Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. About The Company We're Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM and pioneering the next frontier of enterprise AI with AgentForce. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. About The Team Join the Marketing AI/ML Algorithms and Applications team within Salesforce's Marketing organization. In this role, you'll have the opportunity to make an outsized impact on Salesforce's marketing initiatives, helping to promote our vast product portfolio to a global customer base, including 90% of the Fortune 500. By driving state-of-the-art ML solutions for our internal marketing platforms, you'll directly contribute to enhancing the effectiveness of Salesforce's marketing efforts. Your ML expertise will play a pivotal role in accelerating Salesforce's growth. This is a unique chance to apply your passion for ML to drive transformative business impact on a global scale, shaping the future of how Salesforce engages with potential and existing customers, and contributing to our continued innovation and industry leadership in the CRM and Agentic enterprise space. About The Role We are seeking an experienced Lead / Staff Machine Learning Engineer to support the development and deployment of high-impact ML model pipelines that measurably improve marketing performance and deliver customer value. In this critical role, you will collaborate closely with Data Science, Data Engineering, Product, and Marketing teams to lead the design, implementation, and operations of end-to-end ML solutions at scale. As a hands-on technical leader, you will own the MLOps lifecycle, establish best practices, and mentor junior engineers to help grow a world-class team that stays at the forefront of ML innovation. This is a unique opportunity to apply your passion for ML and to drive transformative business impact for the world's #1 CRM provider, shaping the future of customer engagement through AgentForce - our groundbreaking AI agents that are setting new global standards for intelligent automation. Responsibilities Define and drive the technical ML strategy with emphasis on robust, performant model architectures and MLOps practices Lead end-to-end ML pipeline development focusing on automated retraining workflows and model optimization for cost and performance Implement infrastructure-as-code, CI/CD pipelines, and MLOps automation with focus on model monitoring and drift detection Own the MLOps lifecycle including model governance, testing standards, and incident response for production ML systems Establish and enforce engineering standards for model deployment, testing, version control, and code quality Design and implement comprehensive monitoring solutions for model performance, data quality, and system health Collaborate with Data Science, Data Engineering, and Product Management teams to deliver scalable ML solutions with measurable impact Provide technical leadership in ML engineering best practices and mentor junior engineers in MLOps principles Position Requirements 8+ years of experience building and deploying ML model pipelines at scale, with focus on marketing use cases Expert-level knowledge of AWS services, particularly SageMaker and MLflow, for comprehensive ML experiment tracking and model lifecycle management Deep expertise in containerisation and workflow orchestration (Docker, Kubernetes, Apache Airflow) for ML pipeline automation Advanced Python programming with expertise in ML frameworks (TensorFlow, PyTorch) and software engineering best practices Proven experience implementing end-to-end MLOps practices including CI/CD, testing frameworks, and model monitoring Strong background in feature engineering and feature store implementations using cloud-native technologies Expert in infrastructure-as-code, monitoring solutions, and big data technologies (Spark, Snowflake) Experience defining ML governance policies and ensuring compliance with data security requirements Track record of leading ML initiatives that deliver measurable marketing impact Strong collaboration skills and ability to work effectively with Data Science and Platform Engineering teams Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

TCS HIRING!! ROLE: AWS Data Architect YEAR OF EXP: 8 + YEARS LOCATION: Chennai/ Pune / Bangalore / Hyd Data Architect: Must have: Relational SQL/ Caching expertise – Deep knowledge of Amazon Aurora PostgreSQL, ElastiCache etc.. Data modeling – Experience in OLTP and OLAP schemas, normalization, denormalization, indexing, and partitioning. Schema design & migration – Defining best practices for schema evolution when migrating from SQL Server to PostgreSQL. Data governance – Designing data lifecycle policies, archival strategies, and regulatory compliance frameworks. AWS Glue & AWS DMS – Leading data migration strategies to Aurora PostgreSQL. ETL & Data Pipelines – Expertise in Extract, Transform, Load (ETL) workflows . Glue jobs features and event-driven architectures. Data transformation & mapping – PostgreSQL PL/pgSQL migration / transformation expertise while ensuring data integrity. Cross-platform data integration – Connecting cloud and on-premises / other cloud data sources. AWS Data Services – Strong experience in S3, Glue, Lambda, Redshift, Athena, and Kinesis. Infrastructure as Code (IaC) – Using Terraform, CloudFormation, or AWS CDK for database provisioning. Security & Compliance – Implementing IAM, encryption (AWS KMS), access control policies, and compliance frameworks (eg. GDPR ,PII). Query tuning & indexing strategies – Optimizing queries for high performance. Capacity planning & scaling – Ensuring high availability, failover mechanisms, and auto-scaling strategies. Data partitioning & storage optimization – Designing cost-efficient hot/cold data storage policies. Should have experience with setting up the AWS architecture as per the project requirements Good to have: Data Warehousing – Expertise in Amazon Redshift, Snowflake, or BigQuery. Big Data Processing – Familiarity with Apache Spark, EMR, Hadoop, or Kinesis. Data Lakes & Analytics – Experience in AWS Lake Formation, Glue Catalog, and Athena. Machine Learning Pipelines – Understanding of SageMaker, BedRock etc. for AI-driven analytics. CI/CD for Data Pipelines – Knowledge of AWS CodePipeline, Jenkins, or GitHub Actions. Serverless Data Architectures – Experience with event-driven systems (SNS, SQS, Step Functions). Show more Show less

Job Summary: We are seeking a highly skilled and experienced Data Scientist with a deep understanding of data analytics powered by artificial intelligence (AI) tools. The ideal candidate will be passionate about turning data into actionable insights using cutting-edge AI platforms, automation techniques, and advanced statistical methods. Key Responsibilities: Develop and deploy scalable AI-powered data analytics solutions for business intelligence, forecasting, and optimization. Leverage AI tools to automate data cleansing, feature engineering, model building, and visualization. Design and conduct advanced statistical analyses and machine learning models (supervised, unsupervised, NLP, etc.). Collaborate cross-functionally with engineering and business teams to drive data-first decision-making. Must-Have Skills & Qualifications: Minimum 4 years of professional experience in data science, analytics, or a related field. Proficiency in Python and/or R with strong hands-on experience in ML libraries (scikit-learn, XGBoost, TensorFlow, etc.). Expert knowledge of SQL and working with relational databases. Proven experience with data wrangling, data pipelines, and ETL processes. Deep Understanding of AI Tools for Data Analytics (Experience with several of the following is required): Data Preparation & Automation: Alteryx, Trifacta, KNIME AI/ML Platforms: DataRobot, H2O.ai, Amazon SageMaker, Azure ML Studio, Google Vertex AI Visualization & BI: Tableau, Power BI, Looker (with AI/ML integrations) AutoML & Predictive Modeling: Google AutoML, IBM Watson Studio, BigML NLP & Text Analytics: OpenAI (ChatGPT, Codex APIs), Hugging Face Transformers, MonkeyLearn Workflow Orchestration: Apache Airflow, Prefect Preferred Qualifications: Degree in Computer Science, Data Science, Statistics, or related field. Experience in cloud-based environments (AWS, GCP, Azure) for ML workloads. To apply, please send your resume to sooraj@superpe.in or shreya@superpe.in SuperPe is an equal opportunity employer and welcomes candidates of all backgrounds to apply. We look forward to hearing from you! Show more Show less

About the job About us We are surrounded by the world's leading consumer companies led by technology - Amazon for retail, Airbnb for hospitality, Uber for mobility, Netflix and Spotify for entertainment, etc. Food & Beverage is the only consumer sector where large players are still traditional restaurant companies. At Rebel Foods, we are challenging this status quo as we are building the world's most valuable restaurant company on the internet, superfast. The opportunity for us is immense due to the exponential growth in the food delivery business worldwide which has helped us build 'The World's Largest Internet Restaurant Company' in the last few years. Rebel Foods' current presence is India, Indonesia, UAE, UK & KSA with close to 50 brands and 4500+ internet restaurants has been built on The Rebel Operating System . While for us it is still Day 1, we know we are in the middle of a revolution towards creating never seen before customer-first experiences. We bring you a once-in-a-lifetime opportunity to disrupt the 500-year-old industry with technology at its core. Job Description We are looking f or a Data Scienti st-II to join our Data Science & Analytics (DSA) Team. You will get to work with other data scientists, analysts, data engineers, PMs and business teams on some of the toughest and most interesting problems in our industry. Our work spans across areas of inventory forecasting, order predictions, marketing spend optimization, delivery time prediction, personalization, customer insighting, product recommendations, supply chain planning, capacity optimization, and more. The role will involve understanding business problems, designing relevant ML solutions, building & deploying new models, maintaining & enhancing existing models, and automating performance measurement of the same. We are looking for someone who is excited to work in a fast-growing industry, has a spirit of ownership & collaboration, and loves seeing the impact of what they have built at scale! What our team owns at Rebel, the Data Science & Analytics team builds and maintains all ML models, rule-based intelligence, automated reports and dashboards used by the organization. We are on a mission to drive business impact via ML and Data Science and grow adoption of these areas at Rebel. We also want to enable the organization to better understand and effectively use ML and DS. We interact with teams across every business area such as Supply, Operations, Demand Generation, D2C, Finance, Brands, Customer Delight, Central Planning and many more. We are never short of interesting challenges and we balance delivering continuous impact and great CX, while building strong foundations to drive sustainable ML returns overtime. Specific Qualifications Strong working knowledge of a variety of machine learning techniques (Regression, Classification,Clustering, Decision Tree, Probability Networks, Neural Networks, Bayesian models etc.) Proficient in Python, SQL, and machine learning libraries (e.g., TensorFlow,scikit-learn). Experience in working with varied data types (structured and unstructured) and databases Experience with Machine Learning and related technologies such as Python, Tensorflow, Amazon SageMaker Excellent problem-solving skills with a demonstrated ability to think analytically and strategically. Good-to-have Experience solving NLP-based problems or working with LLMs / prompt engineering Working with non-tech stakeholders and explaining ML performance in simple language A love of food (Yes, we have regular tasting sessions at office!) Share across your cv's to v-noor.fazilath@rebelfoods.com Show more Show less

A minimum for 5+ years experience is required. Candidate should have strong hands on expertise in: ML concepts AWS SageMaker Gen AI models Data storage/ Data security /Entity matching Fraud detection/Transaction matching Show more Show less

Role Description UST is seeking an experienced Data Scientist to join our Data & Analytics team. Key Responsibilities Drive client engagement fully and align the development team towards a technical roadmap. Implement analytical requirements by defining and analysing system problems, designing and testing standards and solutions. Develop solution by preparing and evaluating alternative workflow solutions. Determine operational objectives by studying business functions; gathering information; evaluating output requirements and formats. Design new analytical solutions by analysing requirements; constructing workflow charts and diagrams; studying system capabilities; writing specifications. Improve systems by studying current practices, designing modifications. Recommends controls by identifying problems, writing improved procedures. Define project requirements by identifying project milestones, phases, and elements; forming project team; establishing project budget. Monitor project progress by tracking activity; resolving problems; publishing progress reports; recommending actions. Maintain system protocols by writing and updating procedures. Provide references for users by writing and maintaining user documentation; providing help desk support; training users. Maintain user confidence and protects operations by keeping information confidential. Prepare technical reports by collecting, analysing, and summarizing information and trends. Maintain professional and technical knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; benchmarking state-of-the-art practices; participating in professional societies. Required Skills And Experience Professional experience of 10+ years in business analysis, requirement gathering, solution workflow design for AI/ML/Analytics project. Excellent problem solving, Critical and Analytical thinking skills and hands on coding skills. Proficient in Data fetch, data merge, data wrangling, exploratory data analysis and feature engineering. Experience in programming skills in Python and SQL with working knowledge of machine learning algorithms. Strong understanding of ML libraries and applications e.g., Time series analysis, Neural Net, SVMs, boosting methods and implementation using Python. Experience in Deep learning techniques. Excellent Communication skills to effectively collaborate with business SMEs, UX team. Intermediate knowledge with Dev Ops practices, including CICD, Automation, Build Management, and Versioning. Understanding of Cloud services, including Azure ML or AWS Sagemaker or GCP Vertex AI. Experience in LLM/Gen AI – Prompt Engineering, RAG and parameter hypertuning. Experience in Pyspark will be an added advantage. Skills MS Azure,Azure Cloud,Azure Data Factory,Data Scientist Show more Show less

Our people work differently depending on their jobs and needs. From hybrid working to flexible hours, we have plenty of options that help our people to thrive. This role is based in India and as such all normal working days must be carried out in India. Job Description Join us as a Machine Learning Engineer In this role, you’ll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms Day-to-day, you’ll make sure that models and algorithms work effectively in a production environment while promoting data literacy education with business stakeholders If you see opportunities where others see challenges, you’ll find that this solutions-driven role will be your chance to solve new problems and enjoy excellent career development What you’ll do Your daily responsibilities will include you collaborating with colleagues to design and develop advanced machine learning products which power our group for our customers. You’ll also codify and automate complex machine learning model productions, including pipeline optimisation. We’ll expect you to transform advanced data science prototypes and apply machine learning algorithms and tools. You’ll also plan, manage, and deliver larger or complex projects, involving a variety of colleagues and teams across our business. You’ll also be responsible for: Understanding the complex requirements and needs of business stakeholders, developing good relationships and how machine learning solutions can support our business strategy Working with colleagues to productionise machine learning models, including pipeline design and development and testing and deployment, so the original intent is carried over to production Creating frameworks to ensure robust monitoring of machine learning models within a production environment, making sure they deliver quality and performance Understanding and addressing any shortfalls, for instance, through retraining Leading direct reports and wider teams in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and Scrum outcomes The skills you’ll need To be successful in this role, you’ll need to have a good academic background in a STEM discipline, such as Mathematics, Physics, Engineering or Computer Science. You’ll also have the ability to use data to solve business problems, from hypotheses through to resolution. We’ll look to you to have experience of at least twelve years with machine learning on large datasets, as well as experience building, testing, supporting, and deploying advanced machine learning models into a production environment using modern CI/CD tools, including git, TeamCity and CodeDeploy. You’ll also need: A good understanding of machine learning approaches and algorithms such as supervised or unsupervised learning, deep learning, NLP with a strong focus on model development, deployment, and optimization Experience using Python with libraries such as NumPy, Pandas, Scikit-learn, and TensorFlow or PyTorch An understanding of PySpark for distributed data processing and manipulation with AWS (Amazon Web Services) including EC2, S3, Lambda, SageMaker, and other cloud tools. Experience with data processing frameworks such as Apache Kafka, Apache Airflow and containerization technologies such as Docker and orchestration tools such as Kubernetes Experience of building GenAI solutions to automate workflows to improve productivity and efficiency Show more Show less

About The Role We’re looking for top-tier AI/ML Engineers with 6+ years of experience to join our fast-paced and innovative team. If you thrive at the intersection of GenAI, Machine Learning, MLOps, and application development, we want to hear from you. You’ll have the opportunity to work on high-impact GenAI applications and build scalable systems that solve real business problems. Key Responsibilities Design, develop, and deploy GenAI applications using techniques like RAG (Retrieval Augmented Generation), prompt engineering, model evaluation, and LLM integration. Architect and build production-grade Python applications using frameworks such as FastAPI or Flask. Implement gRPC services, event-driven systems (Kafka, PubSub), and CI/CD pipelines for scalable deployment. Collaborate with cross-functional teams to frame business problems as ML use-cases — regression, classification, ranking, forecasting, and anomaly detection. Own end-to-end ML pipeline development: data preprocessing, feature engineering, model training/inference, deployment, and monitoring. Work with tools such as Airflow, Dagster, SageMaker, and MLflow to operationalize and orchestrate pipelines. Ensure model evaluation, A/B testing, and hyperparameter tuning is done rigorously for production systems. Must-Have Skills Hands-on experience with GenAI/LLM-based applications – RAG, Evals, vector stores, embeddings. Strong backend engineering using Python, FastAPI/Flask, gRPC, and event-driven architectures. Experience with CI/CD, infrastructure, containerization, and cloud deployment (AWS, GCP, or Azure). Proficient in ML best practices: feature selection, hyperparameter tuning, A/B testing, model explainability. Proven experience in batch data pipelines and training/inference orchestration. Familiarity with tools like Airflow/Dagster, SageMaker, and data pipeline architecture. Show more Show less

🚨 We are Hiring 🚨 https://grhombustech.com/jobs/job-description-senior-test-automation-lead-playwright-ai-ml-focus/ Job Description Job Title: Senior Test Automation Lead – Playwright (AI/ML Focus) Location: Hyderabad Job Type: Full-Time Company Overview: GRhombus Technologies Pvt Ltd, a pioneer in Software Solutions – Especially on Test Automation, Cyber Security, Full Stack Development, DevOps, Salesforce, Performance Testing and Manual Testing. GRhombus delivery centres are located in India at Hyderabad, Chennai, Bengaluru and Pune. In the Middle East, we are located in Dubai. Our partner offices are located in the USA and the Netherlands. About the Role: We are seeking a passionate and technically skilled Senior Test Automation Lead with deep experience in Playwright-based frameworks and a solid understanding of AI/ML-driven applications. In this role, you will lead the automation strategy and quality engineering practices for next-generation AI products that integrate large-scale machine learning models, data pipelines, and dynamic, intelligent UIs. You will define, architect, and implement scalable automation solutions across AI-enhanced features such as recommendation engines, conversational UIs, real-time analytics, and predictive workflows, ensuring both functional correctness and intelligent behavior consistency. Key Responsibilities: Test Automation Framework Design & Implementation Design and implement robust, modular, and extensible Playwright automation frameworks using TypeScript/JavaScript. Define automation design patterns and utilities that can handle complex AI-driven UI behaviors (e.g., dynamic content, personalization, chat interfaces). Implement abstraction layers for easy test data handling, reusable components, and multi-browser/platform execution. AI/ML-Specific Testing Strategy Partner with Data Scientists and ML Engineers to understand model behaviors, inference workflows, and output formats. Develop strategies for testing non-deterministic model outputs (e.g., chat responses, classification labels) using tolerance ranges, confidence intervals, or golden datasets. Design tests to validate ML integration points: REST/gRPC API calls, feature flags, model versioning, and output accuracy. Include bias, fairness, and edge-case validations in test suites where applicable (e.g., fairness in recommendation engines or NLP sentiment analysis). End-to-End Test Coverage Lead the implementation of end-to-end automation for: Web interfaces (React, Angular, or other SPA frameworks) Backend services (REST, GraphQL, WebSockets) ML model integration endpoints (real-time inference APIs, batch pipelines) Build test utilities for mocking, stubbing, and simulating AI inputs and datasets. CI/CD & Tooling Integration Integrate automation suites into CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI, or similar. Configure parallel execution, containerized test environments (e.g., Docker), and test artifact management. Establish real-time dashboards and historical reporting using tools like Allure, ReportPortal, TestRail, or custom Grafana integrations. Quality Engineering & Leadership Define KPIs and QA metrics for AI/ML product quality: functional accuracy, model regression rates, test coverage %, time-to-feedback, etc. Lead and mentor a team of automation and QA engineers across multiple projects. Act as the Quality Champion across the AI platform by influencing engineering, product, and data science teams on quality ownership and testing best practices. Agile & Cross-Functional Collaboration Work in Agile/Scrum teams; participate in backlog grooming, sprint planning, and retrospectives. Collaborate across disciplines: Frontend, Backend, DevOps, MLOps, and Product Management to ensure complete testability. Review feature specs, AI/ML model update notes, and data schemas for impact analysis. Required Skills and Qualifications: Technical Skills: Strong hands-on expertise with Playwright (TypeScript/JavaScript). Experience building custom automation frameworks and utilities from scratch. Proficiency in testing AI/ML-integrated applications: inference endpoints, personalization engines, chatbots, or predictive dashboards. Solid knowledge of HTTP protocols, API testing (Postman, Supertest, RestAssured). Familiarity with MLOps and model lifecycle management (e.g., via MLflow, SageMaker, Vertex AI). Experience in testing data pipelines (ETL, streaming, batch), synthetic data generation, and test data versioning. Domain Knowledge: Exposure to NLP, CV, recommendation engines, time-series forecasting, or tabular ML models. Understanding of key ML metrics (precision, recall, F1-score, AUC), model drift, and concept drift. Knowledge of bias/fairness auditing, especially in UI/UX contexts where AI decisions are shown to users. Leadership & Communication: Proven experience leading QA/Automation teams (4+ engineers). Strong documentation, code review, and stakeholder communication skills. Experience collaborating in Agile/SAFe environments with cross-functional teams. Preferred Qualifications: Experience with AI Explainability frameworks like LIME, SHAP, or What-If Tool. Familiarity with Test Data Management platforms (e.g., Tonic.ai, Delphix) for ML training/inference data. Background in performance and load testing for AI systems using tools like Locust, JMeter, or k6. Experience with GraphQL, Kafka, or event-driven architecture testing. QA Certifications (ISTQB, Certified Selenium Engineer) or cloud certifications (AWS, GCP, Azure). Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related technical discipline. Bonus for certifications or formal training in Machine Learning, Data Science, or MLOps. Why Join Us? At GRhombus, we are redefining quality assurance and software testing with cutting-edge methodologies and a commitment to innovation. As a test automation lead, you will play a pivotal role in shaping the future of automated testing, optimizing frameworks, and driving efficiency across our engineering ecosystem. Be part of a workplace that values experimentation, learning, and professional growth. Contribute to an organisation where your ideas drive innovation and make a tangible impact. Show more Show less

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Cloud AI Engineer The opportunity We are the only professional services organization who has a separate business dedicated exclusively to the financial services marketplace. Join Digital Engineering Team and you will work with multi-disciplinary teams from around the world to deliver a global perspective. Aligned to key industry groups including Asset management, Banking and Capital Markets, Insurance and Private Equity, Health, Government, Power and Utilities, we provide integrated advisory, assurance, tax, and transaction services. Through diverse experiences, world-class learning and individually tailored coaching you will experience ongoing professional development. That’s how we develop outstanding leaders who team to deliver on our promises to all our stakeholders, and in so doing, play a critical role in building a better working world for our people, for our clients and for our communities. Sound interesting? Well, this is just the beginning. Because whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. We are looking for a talented and motivated AI Engineer to join our team and work alongside our AI Architect. The ideal candidate will have a strong background in AI/ML, data engineering, and cloud technologies, with a focus on AI & Generative AI (GenAI) technologies. You will be responsible for developing, deploying, and optimizing AI models and solutions, ensuring they meet the performance, scalability, and security requirements of our organization. EY Digital Engineering is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional capability and product knowledge. The Digital Engineering practice works with clients to analyse, formulate, design, mobilize and drive digital transformation initiatives. We advise clients on their most pressing digital challenges and opportunities surround business strategy, customer, growth, profit optimization, innovation, technology strategy, and digital transformation. We also have a unique ability to help our clients translate strategy into actionable technical design, and transformation planning/mobilization. Through our unique combination of competencies and solutions, EY’s DE team helps our clients sustain competitive advantage and profitability by developing strategies to stay ahead of the rapid pace of change and disruption and supporting the execution of complex transformations. Your Key Responsibilities AI/ML Model Development Develop and train machine learning models using frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn. Leverage large language models (LLMs) and work on cloud LLM deployments. Build AI agents and have a solid understanding of agentic frameworks. Implement and fine-tune AI models for various business applications. AI/ML Deployment and Optimization Deploy machine learning models on cloud platforms (e.g., AWS, Azure, GCP). Optimize AI pipelines for both real-time and batch processing. Understand concepts around model fine-tuning, distillation, and optimization. Monitor and maintain the performance of deployed models, ensuring they meet business requirements. Cloud Integration Integrate AI/ML models with existing cloud infrastructure. Utilize cloud services (e.g., AWS SageMaker, Azure AI, GCP AI Hub) to manage AI workloads. Ensure compliance with data privacy and security standards. Collaboration and Support Work closely with the AI Architect to design scalable AI solutions. Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders. Provide technical support and troubleshooting for AI-related issues. Continuous Learning and Innovation Stay updated on the latest advancements in AI/ML technologies. Experiment with new AI tools and frameworks to enhance existing solutions. Contribute to the adoption of best practices for AI model lifecycle management. Skills And Attributes For Success Proficiency in AI/ML frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn. Experience with cloud platforms: AWS, Azure, GCP. Understanding of data engineering, ETL pipelines, and big data tools (e.g., Apache Spark, Hadoop). Hands-on experience with containerization and orchestration tools (Docker, Kubernetes). Knowledge of DevOps practices for AI/ML (MLOps). Strong understanding of deep learning models, including DNN, LSTM, Transformers, RL, and GNN. Experience with Generative AI technologies, including LLMs, model fine-tuning, distillation, and optimization. Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced, collaborative environment. Preferred Qualifications: Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure AI Engineer) are a plus. Experience: At least 5+ years in AI-related roles Proven experience in developing and deploying AI solutions with Python, JavaScript Strong background in machine learning, deep learning, and data modelling. Experience in integrating AI models with cloud infrastructure. Agile Methodologies: Familiarity with Agile development practices and methodologies. Education: Bachelor’s or master’s degree in computer science, Engineering, or a related field. What We Offer EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations – Argentina, China, India, the Philippines, Poland and the UK – and with teams from all EY service lines, geographies and sectors, playing a vital role in the delivery of the EY growth strategy. From accountants to coders to advisory consultants, we offer a wide variety of fulfilling career opportunities that span all business disciplines. In GDS, you will collaborate with EY teams on exciting projects and work with well-known brands from across the globe. We’ll introduce you to an ever-expanding ecosystem of people, learning, skills and insights that will stay with you throughout your career. Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next. Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way. Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs. Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Cloud AI Engineer The opportunity We are the only professional services organization who has a separate business dedicated exclusively to the financial services marketplace. Join Digital Engineering Team and you will work with multi-disciplinary teams from around the world to deliver a global perspective. Aligned to key industry groups including Asset management, Banking and Capital Markets, Insurance and Private Equity, Health, Government, Power and Utilities, we provide integrated advisory, assurance, tax, and transaction services. Through diverse experiences, world-class learning and individually tailored coaching you will experience ongoing professional development. That’s how we develop outstanding leaders who team to deliver on our promises to all our stakeholders, and in so doing, play a critical role in building a better working world for our people, for our clients and for our communities. Sound interesting? Well, this is just the beginning. Because whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. We are looking for a talented and motivated AI Engineer to join our team and work alongside our AI Architect. The ideal candidate will have a strong background in AI/ML, data engineering, and cloud technologies, with a focus on AI & Generative AI (GenAI) technologies. You will be responsible for developing, deploying, and optimizing AI models and solutions, ensuring they meet the performance, scalability, and security requirements of our organization. EY Digital Engineering is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional capability and product knowledge. The Digital Engineering practice works with clients to analyse, formulate, design, mobilize and drive digital transformation initiatives. We advise clients on their most pressing digital challenges and opportunities surround business strategy, customer, growth, profit optimization, innovation, technology strategy, and digital transformation. We also have a unique ability to help our clients translate strategy into actionable technical design, and transformation planning/mobilization. Through our unique combination of competencies and solutions, EY’s DE team helps our clients sustain competitive advantage and profitability by developing strategies to stay ahead of the rapid pace of change and disruption and supporting the execution of complex transformations. Your Key Responsibilities AI/ML Model Development Develop and train machine learning models using frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn. Leverage large language models (LLMs) and work on cloud LLM deployments. Build AI agents and have a solid understanding of agentic frameworks. Implement and fine-tune AI models for various business applications. AI/ML Deployment and Optimization Deploy machine learning models on cloud platforms (e.g., AWS, Azure, GCP). Optimize AI pipelines for both real-time and batch processing. Understand concepts around model fine-tuning, distillation, and optimization. Monitor and maintain the performance of deployed models, ensuring they meet business requirements. Cloud Integration Integrate AI/ML models with existing cloud infrastructure. Utilize cloud services (e.g., AWS SageMaker, Azure AI, GCP AI Hub) to manage AI workloads. Ensure compliance with data privacy and security standards. Collaboration and Support Work closely with the AI Architect to design scalable AI solutions. Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders. Provide technical support and troubleshooting for AI-related issues. Continuous Learning and Innovation Stay updated on the latest advancements in AI/ML technologies. Experiment with new AI tools and frameworks to enhance existing solutions. Contribute to the adoption of best practices for AI model lifecycle management. Skills And Attributes For Success Proficiency in AI/ML frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn. Experience with cloud platforms: AWS, Azure, GCP. Understanding of data engineering, ETL pipelines, and big data tools (e.g., Apache Spark, Hadoop). Hands-on experience with containerization and orchestration tools (Docker, Kubernetes). Knowledge of DevOps practices for AI/ML (MLOps). Strong understanding of deep learning models, including DNN, LSTM, Transformers, RL, and GNN. Experience with Generative AI technologies, including LLMs, model fine-tuning, distillation, and optimization. Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced, collaborative environment. Preferred Qualifications: Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure AI Engineer) are a plus. Experience: At least 5+ years in AI-related roles Proven experience in developing and deploying AI solutions with Python, JavaScript Strong background in machine learning, deep learning, and data modelling. Experience in integrating AI models with cloud infrastructure. Agile Methodologies: Familiarity with Agile development practices and methodologies. Education: Bachelor’s or master’s degree in computer science, Engineering, or a related field. What We Offer EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations – Argentina, China, India, the Philippines, Poland and the UK – and with teams from all EY service lines, geographies and sectors, playing a vital role in the delivery of the EY growth strategy. From accountants to coders to advisory consultants, we offer a wide variety of fulfilling career opportunities that span all business disciplines. In GDS, you will collaborate with EY teams on exciting projects and work with well-known brands from across the globe. We’ll introduce you to an ever-expanding ecosystem of people, learning, skills and insights that will stay with you throughout your career. Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next. Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way. Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs. Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

About The Chatterjee Group The Chatterjee Group (TCG) has an enviable track record as a strategic investor, with businesses in many sectors. Founded by Dr. Purnendu Chatterjee in 1989, the Group specializes in the Petrochemicals, Pharmaceuticals, Biotech, Financial Services, Real Estate and Technology sectors in the US, Europe and South Asia. It provides end-to-end product and service capabilities through its investments and companies in these sectors. TCG is one of the biggest PE groups in the country with significant brand presence abroad and in India. About The Company – First Livingspaces First Livingspaces is a fully owned subsidiary of the TCG group. First Livingspaces is an AI first company which intends to create an ecosystem for daily living needs and necessities. We want to simplify the life of an individual who intends to rent, buy or Co-live, and provide all amenities for a happy seamless living. We are building a large universe, powered by technology at the core. About The Role In this senior role, you will lead the development and implementation of MLOps strategies for our AI/ML systems within India's first real estate ecosystem. You will manage the entire ML model lifecycle, ensuring scalability, reliability, and performance from development to production. You will collaborate with data science and engineering teams, define and implement MLOps best practices, and take ownership of the ML infrastructure. Your technical expertise will be crucial in building robust MLOps systems that deliver reliable results at scale. Responsibilities Architect and implement CI/CD pipelines for ML models using PyTorch or TensorFlow. Design and build infrastructure for model versioning, deployment, monitoring, and scaling. Implement and maintain feature stores (Feast, Tecton) and experiment tracking(MLflow, Weights & Biases). Enable continuous training and monitoring with tools like SageMaker Model Monitor, Evidently, etc. Develop and deploy ML model registries and automated model serving solutions. Collaborate with data science and engineering teams to transition from experimentation to production. Establish infrastructure-as-code practices using Terraform, Pulumi, or CloudFormation. Technical Requirements 5+ years of experience in MLOps, DevOps, or related fields, with at least 2 years in a senior role. MLOps Tools: MLflow, Kubeflow Mastery of CI/CD tools (GitHub Actions, Jenkins, ArgoCD, Tekton). Expertise with infrastructure-as-code (Terraform, Pulumi, CloudFormation) and GitOps practices. Knowledge of containerization (Docker) and orchestration (Kubernetes, EKS, GKE, AKS). Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). Experience with ML deployment frameworks (TensorFlow Serving, TorchServe, KServe, BentoML, NVIDIA Triton). Why Join Us? Work on impactful projects leveraging cutting-edge AI technologies. Your work here won’t sit in a sandbox — see your models deployed at scale, making a tangible difference in the real world. Competitive compensation, perks, and a flexible, inclusive work environment. Inclusive and Equal Workplace First Livingspaces is dedicated to creating an inclusive workplace that promotes equality and fairness. We celebrate diversity and ensure that no one is discriminated against based on gender, caste, race, religion, sexual orientation, protected veteran status, disability, age, or any other characteristic, fostering an environment where everyone can thrive. Show more Show less