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

Every second, the internet gets messier. Content floods in from humans and machines alike—some helpful, some harmful, and most of it unstructured. Forums, blogs, knowledge bases, event pages, community threads: these are the lifeblood of digital platforms, but they also carry risk. Left unchecked, they can drift into chaos, compromise brand integrity, or expose users to misinformation and abuse. The scale is too big for humans alone, and AI isn’t good enough to do it alone—yet. That’s where we come in. Our team is rebuilding content integrity from the ground up by combining human judgment with generative AI. We don’t treat AI like a sidekick or a threat. Every moderator on our team works side-by-side with GenAI tools to classify, tag, escalate, and refine content decisions at speed. The edge cases you annotate and the feedback you give train smarter systems, reduce false positives, and make AI moderation meaningfully better with every cycle. This isn’t a job where you manually slog through a never-ending moderation queue. It’s not an outsourced content cop role. You’ll spend your days interacting directly with AI to make decisions, flag patterns, streamline workflows, and make sure the right content sees the light of day. If you’re the kind of person who thrives on structured work, enjoys hunting down ambiguity, and finds satisfaction in operational clarity, this job will feel like a control panel for the future of content quality. You’ll be joining a team obsessed with platform integrity and operational scale. Your job is to keep the machine running smoothly: managing queues, moderating edge cases, annotating training data, and making feedback loops tighter and faster. If you’ve used tools like ChatGPT to get real work done—not just writing poems or brainstorming ideas, but actually processing or classifying information—this is your next level. What You Will Be Doing Review and moderate user- and AI-generated content using GenAI tools to enforce platform policies and maintain a safe, high-quality environment Coordinate content workflows across tools and teams, ensuring timely processing, clear tracking, and smooth handoffs Tag edge cases, annotate training data, and provide structured feedback to improve the accuracy and performance of AI moderation systems What You Won’t Be Doing A boring content moderation job focused on manually reviewing of blogpost after blogpost An entry-level admin role with low agency or impact, just checking boxes in a queue Basic Requirements AI Content Reviewer key responsibilities At least 1 year of professional work experience Hands-on experience using GenAI tools (e.g., ChatGPT, Claude, Gemini) in a professional, academic, or personal productivity context Strong English writing skills About IgniteTech If you want to work hard at a company where you can grow and be a part of a dynamic team, join IgniteTech! Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally. We’re doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility. A career with IgniteTech is challenging and fast-paced. We are always looking for energetic and enthusiastic employees to join our world-class team. We offer opportunities for personal contribution and promote career development. IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace. There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! Working with us This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $15 USD/hour, which equates to $30,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic. Crossover Job Code: LJ-5593-IN-Chennai-AIContentRevie.002 Show more Show less

Every second, the internet gets messier. Content floods in from humans and machines alike—some helpful, some harmful, and most of it unstructured. Forums, blogs, knowledge bases, event pages, community threads: these are the lifeblood of digital platforms, but they also carry risk. Left unchecked, they can drift into chaos, compromise brand integrity, or expose users to misinformation and abuse. The scale is too big for humans alone, and AI isn’t good enough to do it alone—yet. That’s where we come in. Our team is rebuilding content integrity from the ground up by combining human judgment with generative AI. We don’t treat AI like a sidekick or a threat. Every moderator on our team works side-by-side with GenAI tools to classify, tag, escalate, and refine content decisions at speed. The edge cases you annotate and the feedback you give train smarter systems, reduce false positives, and make AI moderation meaningfully better with every cycle. This isn’t a job where you manually slog through a never-ending moderation queue. It’s not an outsourced content cop role. You’ll spend your days interacting directly with AI to make decisions, flag patterns, streamline workflows, and make sure the right content sees the light of day. If you’re the kind of person who thrives on structured work, enjoys hunting down ambiguity, and finds satisfaction in operational clarity, this job will feel like a control panel for the future of content quality. You’ll be joining a team obsessed with platform integrity and operational scale. Your job is to keep the machine running smoothly: managing queues, moderating edge cases, annotating training data, and making feedback loops tighter and faster. If you’ve used tools like ChatGPT to get real work done—not just writing poems or brainstorming ideas, but actually processing or classifying information—this is your next level. What You Will Be Doing Review and moderate user- and AI-generated content using GenAI tools to enforce platform policies and maintain a safe, high-quality environment Coordinate content workflows across tools and teams, ensuring timely processing, clear tracking, and smooth handoffs Tag edge cases, annotate training data, and provide structured feedback to improve the accuracy and performance of AI moderation systems What You Won’t Be Doing A boring content moderation job focused on manually reviewing of blogpost after blogpost An entry-level admin role with low agency or impact, just checking boxes in a queue Basic Requirements AI Content Reviewer key responsibilities At least 1 year of professional work experience Hands-on experience using GenAI tools (e.g., ChatGPT, Claude, Gemini) in a professional, academic, or personal productivity context Strong English writing skills About IgniteTech If you want to work hard at a company where you can grow and be a part of a dynamic team, join IgniteTech! Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally. We’re doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility. A career with IgniteTech is challenging and fast-paced. We are always looking for energetic and enthusiastic employees to join our world-class team. We offer opportunities for personal contribution and promote career development. IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace. There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! Working with us This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $15 USD/hour, which equates to $30,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic. Crossover Job Code: LJ-5593-IN-NewDelhi-AIContentRevie.002 Show more Show less

Every second, the internet gets messier. Content floods in from humans and machines alike—some helpful, some harmful, and most of it unstructured. Forums, blogs, knowledge bases, event pages, community threads: these are the lifeblood of digital platforms, but they also carry risk. Left unchecked, they can drift into chaos, compromise brand integrity, or expose users to misinformation and abuse. The scale is too big for humans alone, and AI isn’t good enough to do it alone—yet. That’s where we come in. Our team is rebuilding content integrity from the ground up by combining human judgment with generative AI. We don’t treat AI like a sidekick or a threat. Every moderator on our team works side-by-side with GenAI tools to classify, tag, escalate, and refine content decisions at speed. The edge cases you annotate and the feedback you give train smarter systems, reduce false positives, and make AI moderation meaningfully better with every cycle. This isn’t a job where you manually slog through a never-ending moderation queue. It’s not an outsourced content cop role. You’ll spend your days interacting directly with AI to make decisions, flag patterns, streamline workflows, and make sure the right content sees the light of day. If you’re the kind of person who thrives on structured work, enjoys hunting down ambiguity, and finds satisfaction in operational clarity, this job will feel like a control panel for the future of content quality. You’ll be joining a team obsessed with platform integrity and operational scale. Your job is to keep the machine running smoothly: managing queues, moderating edge cases, annotating training data, and making feedback loops tighter and faster. If you’ve used tools like ChatGPT to get real work done—not just writing poems or brainstorming ideas, but actually processing or classifying information—this is your next level. What You Will Be Doing Review and moderate user- and AI-generated content using GenAI tools to enforce platform policies and maintain a safe, high-quality environment Coordinate content workflows across tools and teams, ensuring timely processing, clear tracking, and smooth handoffs Tag edge cases, annotate training data, and provide structured feedback to improve the accuracy and performance of AI moderation systems What You Won’t Be Doing A boring content moderation job focused on manually reviewing of blogpost after blogpost An entry-level admin role with low agency or impact, just checking boxes in a queue Basic Requirements AI Content Reviewer key responsibilities At least 1 year of professional work experience Hands-on experience using GenAI tools (e.g., ChatGPT, Claude, Gemini) in a professional, academic, or personal productivity context Strong English writing skills About IgniteTech If you want to work hard at a company where you can grow and be a part of a dynamic team, join IgniteTech! Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally. We’re doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility. A career with IgniteTech is challenging and fast-paced. We are always looking for energetic and enthusiastic employees to join our world-class team. We offer opportunities for personal contribution and promote career development. IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace. There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! Working with us This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $15 USD/hour, which equates to $30,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic. Crossover Job Code: LJ-5593-IN-Kolkata-AIContentRevie.002 Show more Show less

Every second, the internet gets messier. Content floods in from humans and machines alike—some helpful, some harmful, and most of it unstructured. Forums, blogs, knowledge bases, event pages, community threads: these are the lifeblood of digital platforms, but they also carry risk. Left unchecked, they can drift into chaos, compromise brand integrity, or expose users to misinformation and abuse. The scale is too big for humans alone, and AI isn’t good enough to do it alone—yet. That’s where we come in. Our team is rebuilding content integrity from the ground up by combining human judgment with generative AI. We don’t treat AI like a sidekick or a threat. Every moderator on our team works side-by-side with GenAI tools to classify, tag, escalate, and refine content decisions at speed. The edge cases you annotate and the feedback you give train smarter systems, reduce false positives, and make AI moderation meaningfully better with every cycle. This isn’t a job where you manually slog through a never-ending moderation queue. It’s not an outsourced content cop role. You’ll spend your days interacting directly with AI to make decisions, flag patterns, streamline workflows, and make sure the right content sees the light of day. If you’re the kind of person who thrives on structured work, enjoys hunting down ambiguity, and finds satisfaction in operational clarity, this job will feel like a control panel for the future of content quality. You’ll be joining a team obsessed with platform integrity and operational scale. Your job is to keep the machine running smoothly: managing queues, moderating edge cases, annotating training data, and making feedback loops tighter and faster. If you’ve used tools like ChatGPT to get real work done—not just writing poems or brainstorming ideas, but actually processing or classifying information—this is your next level. What You Will Be Doing Review and moderate user- and AI-generated content using GenAI tools to enforce platform policies and maintain a safe, high-quality environment Coordinate content workflows across tools and teams, ensuring timely processing, clear tracking, and smooth handoffs Tag edge cases, annotate training data, and provide structured feedback to improve the accuracy and performance of AI moderation systems What You Won’t Be Doing A boring content moderation job focused on manually reviewing of blogpost after blogpost An entry-level admin role with low agency or impact, just checking boxes in a queue Basic Requirements AI Content Reviewer key responsibilities At least 1 year of professional work experience Hands-on experience using GenAI tools (e.g., ChatGPT, Claude, Gemini) in a professional, academic, or personal productivity context Strong English writing skills About IgniteTech If you want to work hard at a company where you can grow and be a part of a dynamic team, join IgniteTech! Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally. We’re doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility. A career with IgniteTech is challenging and fast-paced. We are always looking for energetic and enthusiastic employees to join our world-class team. We offer opportunities for personal contribution and promote career development. IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace. There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! Working with us This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $15 USD/hour, which equates to $30,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic. Crossover Job Code: LJ-5593-IN-Mumbai-AIContentRevie.002 Show more Show less

Every second, the internet gets messier. Content floods in from humans and machines alike—some helpful, some harmful, and most of it unstructured. Forums, blogs, knowledge bases, event pages, community threads: these are the lifeblood of digital platforms, but they also carry risk. Left unchecked, they can drift into chaos, compromise brand integrity, or expose users to misinformation and abuse. The scale is too big for humans alone, and AI isn’t good enough to do it alone—yet. That’s where we come in. Our team is rebuilding content integrity from the ground up by combining human judgment with generative AI. We don’t treat AI like a sidekick or a threat. Every moderator on our team works side-by-side with GenAI tools to classify, tag, escalate, and refine content decisions at speed. The edge cases you annotate and the feedback you give train smarter systems, reduce false positives, and make AI moderation meaningfully better with every cycle. This isn’t a job where you manually slog through a never-ending moderation queue. It’s not an outsourced content cop role. You’ll spend your days interacting directly with AI to make decisions, flag patterns, streamline workflows, and make sure the right content sees the light of day. If you’re the kind of person who thrives on structured work, enjoys hunting down ambiguity, and finds satisfaction in operational clarity, this job will feel like a control panel for the future of content quality. You’ll be joining a team obsessed with platform integrity and operational scale. Your job is to keep the machine running smoothly: managing queues, moderating edge cases, annotating training data, and making feedback loops tighter and faster. If you’ve used tools like ChatGPT to get real work done—not just writing poems or brainstorming ideas, but actually processing or classifying information—this is your next level. What You Will Be Doing Review and moderate user- and AI-generated content using GenAI tools to enforce platform policies and maintain a safe, high-quality environment Coordinate content workflows across tools and teams, ensuring timely processing, clear tracking, and smooth handoffs Tag edge cases, annotate training data, and provide structured feedback to improve the accuracy and performance of AI moderation systems What You Won’t Be Doing A boring content moderation job focused on manually reviewing of blogpost after blogpost An entry-level admin role with low agency or impact, just checking boxes in a queue Basic Requirements AI Content Reviewer key responsibilities At least 1 year of professional work experience Hands-on experience using GenAI tools (e.g., ChatGPT, Claude, Gemini) in a professional, academic, or personal productivity context Strong English writing skills About IgniteTech If you want to work hard at a company where you can grow and be a part of a dynamic team, join IgniteTech! Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally. We’re doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility. A career with IgniteTech is challenging and fast-paced. We are always looking for energetic and enthusiastic employees to join our world-class team. We offer opportunities for personal contribution and promote career development. IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace. There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! Working with us This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $15 USD/hour, which equates to $30,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic. Crossover Job Code: LJ-5593-IN-Surat-AIContentRevie.001 Show more Show less

Every second, the internet gets messier. Content floods in from humans and machines alike—some helpful, some harmful, and most of it unstructured. Forums, blogs, knowledge bases, event pages, community threads: these are the lifeblood of digital platforms, but they also carry risk. Left unchecked, they can drift into chaos, compromise brand integrity, or expose users to misinformation and abuse. The scale is too big for humans alone, and AI isn’t good enough to do it alone—yet. That’s where we come in. Our team is rebuilding content integrity from the ground up by combining human judgment with generative AI. We don’t treat AI like a sidekick or a threat. Every moderator on our team works side-by-side with GenAI tools to classify, tag, escalate, and refine content decisions at speed. The edge cases you annotate and the feedback you give train smarter systems, reduce false positives, and make AI moderation meaningfully better with every cycle. This isn’t a job where you manually slog through a never-ending moderation queue. It’s not an outsourced content cop role. You’ll spend your days interacting directly with AI to make decisions, flag patterns, streamline workflows, and make sure the right content sees the light of day. If you’re the kind of person who thrives on structured work, enjoys hunting down ambiguity, and finds satisfaction in operational clarity, this job will feel like a control panel for the future of content quality. You’ll be joining a team obsessed with platform integrity and operational scale. Your job is to keep the machine running smoothly: managing queues, moderating edge cases, annotating training data, and making feedback loops tighter and faster. If you’ve used tools like ChatGPT to get real work done—not just writing poems or brainstorming ideas, but actually processing or classifying information—this is your next level. What You Will Be Doing Review and moderate user- and AI-generated content using GenAI tools to enforce platform policies and maintain a safe, high-quality environment Coordinate content workflows across tools and teams, ensuring timely processing, clear tracking, and smooth handoffs Tag edge cases, annotate training data, and provide structured feedback to improve the accuracy and performance of AI moderation systems What You Won’t Be Doing A boring content moderation job focused on manually reviewing of blogpost after blogpost An entry-level admin role with low agency or impact, just checking boxes in a queue Basic Requirements AI Content Reviewer key responsibilities At least 1 year of professional work experience Hands-on experience using GenAI tools (e.g., ChatGPT, Claude, Gemini) in a professional, academic, or personal productivity context Strong English writing skills About IgniteTech If you want to work hard at a company where you can grow and be a part of a dynamic team, join IgniteTech! Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally. We’re doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility. A career with IgniteTech is challenging and fast-paced. We are always looking for energetic and enthusiastic employees to join our world-class team. We offer opportunities for personal contribution and promote career development. IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace. There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you! Working with us This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $15 USD/hour, which equates to $30,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic. Crossover Job Code: LJ-5593-LK-COUNTRY-AIContentRevie.002 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

Job Title: QA Engineer – Generative AI Testing Location: [Hybrid – Hyderabad/Vishakhapatnam] Job Type: [Full-time] Job Summary: We are seeking a skilled and detail-oriented QA Engineer with expertise in Generative AI Testing to join our team. In this role, you will be responsible for ensuring the accuracy, safety, and performance of AI-driven applications, particularly in the field of Generative AI. You will design and execute test strategies, develop automation frameworks, and validate AI outputs to maintain high-quality user experiences. Key Responsibilities: Design, develop, and execute comprehensive test plans for Generative AI models and applications. Validate AI-generated outputs for accuracy, coherence, bias, ethical considerations, and alignment with business requirements. Develop and maintain automated testing frameworks for AI-based applications, ensuring scalability and efficiency. Perform adversarial testing, edge case analysis, and security testing to assess AI vulnerabilities. Collaborate with AI/ML engineers, product managers, and developers to refine model performance and mitigate errors. Monitor AI model drift and ensure consistent performance across different inputs and datasets. Conduct performance testing to evaluate response times, scalability, and reliability of AI systems. Document test cases, test results, and defects while ensuring compliance with AI governance and ethical guidelines. Continuously explore new tools and methodologies to improve AI testing processes. Requirements: Bachelors or Master’s degree in Computer Science, Engineering, or a related field. 3+ years of experience in Quality Assurance , with at least 1-2 years in AI/ML testing or Generative AI applications. Strong understanding of AI/ML concepts, NLP models, LLMs, and deep learning architectures. Experience with AI testing tools such as LangTest, DeepChecks, Trulens, or custom AI evaluation frameworks . Proficiency in test automation using Python, Selenium, PyTest, or similar frameworks . Familiarity with model evaluation metrics such as BLEU, ROUGE, perplexity, and precision-recall for AI-generated content. Knowledge of bias detection, adversarial testing, and ethical AI considerations. Experience working with APIs, cloud platforms (AWS, Azure, GCP), and MLOps practices. Strong analytical and problem-solving skills with attention to detail. Excellent communication and collaboration skills to work in cross-functional teams. Nice to Have: Experience in testing AI chatbots, voice assistants, or image/video-generating AI. Knowledge of LLM fine-tuning and reinforcement learning from human feedback (RLHF). Exposure to regulatory and compliance frameworks for AI governance. Why Join Us? Opportunity to work on cutting-edge AI products. Collaborate with a team of AI and software experts. Competitive salary, benefits, and career growth opportunities. If you’re interested, Please share your resume with Dkadam@eprosoft.com Show more Show less

Highly skilled Senior Machine Learning Engineer with expertise in Deep Learning, Large Language Models (LLMs), and MLOps/LLMOps to design, optimize, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience in developing and scaling deep learning models, fine-tuning LLMs/ (e.g., GPT, Llama), and implementing robust deployment pipelines for production environments. Responsibilities Model Development & Fine-Tuning: - Design, train, fine-tune and optimize deep learning models (CNNs, RNNs, Transformers) for NLP, computer vision, or multimodal applications. - Fine-tune and adapt Large Language Models (LLMs) for domain-specific tasks (e.g., text generation, summarization, semantic similarity). - Experiment with RLHF (Reinforcement Learning from Human Feedback) and other alignment techniques. Deployment & Scalability (MLOps/LLMOps): - Build and maintain end-to-end ML pipelines for training, evaluation, and deployment. - Deploy LLMs and deep learning models in production environments using frameworks like FastAPI, vLLM, or TensorRT. - Optimize models for low-latency, high-throughput inference (eg., quantization, distillation, etc.). - Implement CI/CD workflows for ML systems using tools like MLflow, Kubeflow. Monitoring & Optimization: - Set up logging, monitoring, and alerting for model performance (drift, latency, accuracy). - Work with DevOps teams to ensure scalability, security, and cost-efficiency of deployed models. Required Skills & Qualifications: - 5-7 years of hands-on experience in Deep Learning, NLP, and LLMs. - Strong proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, and LLM frameworks. - Experience with model deployment tools (Docker, Kubernetes, FastAPI). - Knowledge of MLOps/LLMOps best practices (model versioning, A/B testing, canary deployments). - Familiarity with cloud platforms (AWS, GCP, Azure). Preferred Qualifications: - Contributions to open-source LLM projects. Show more Show less

Job Title : Senior AI/ML Engineer Experience : 5+ Years Location : Remote Job Type - Contractual Job Summary: We are seeking a highly motivated and experienced Senior AI/ML Engineer to join our remote team. In this role, you will design, develop, and deploy cutting-edge AI and machine learning solutions across cloud platforms. The ideal candidate has a passion for innovation, stays up to date with the latest developments in AI, and has hands-on experience with modern AI/ML tools, libraries, and agentic workflows. You will work closely with cross-functional teams to solve complex business problems and drive intelligent automation and decision-making. Key Responsibilities: AI/ML Model Development : Design, build, and deploy robust, scalable machine learning and deep learning models using Python, SQL, NoSQL, and standard ML libraries (e.g., Pandas, Scikit-learn, PyTorch, TensorFlow). Cloud Integration : Leverage cloud-based platforms such as AWS (SageMaker, Bedrock), GCP (Vertex AI, Gemini), Azure AI Studio, and OpenAI to develop and manage end-to-end AI/ML solutions. Model Deployment & Lifecycle Management : Automate deployment pipelines and monitor ML models in production for performance, drift, and retraining needs. Fine-Tuning & Customization : Fine-tune foundation models and LLMs for domain-specific applications using techniques like transfer learning, LoRA, and prompt engineering. Agentic AI Workflows : Implement and optimize agentic workflows involving task-oriented agents and multi-step reasoning pipelines. Architecture & Optimization : Architect data-driven solutions by applying advanced ML, statistical modeling, and deep learning techniques to solve real-world business challenges. Research & Innovation : Stay current with the latest advancements in AI, including GenAI, multi-modal models, RLHF, and experiment with new frameworks and technologies. Cross-Functional Collaboration : Work closely with data scientists, data engineers, product managers, and business stakeholders to translate business requirements into technical solutions. Required Skills & Qualifications: Programming : Expert-level proficiency in Python and SQL; experience working with NoSQL databases. ML/DL Libraries : Strong hands-on experience with Scikit-learn, Pandas, NumPy, TensorFlow, PyTorch. Cloud Platforms : Proven experience with at least one major cloud provider (AWS/GCP/Azure), especially with ML tools like SageMaker, Vertex AI, Bedrock, Azure AI Studio, or OpenAI. Model Deployment : Experience with building, deploying, and monitoring models in production environments. LLMs & Fine-Tuning : Practical experience fine-tuning and integrating large language models (LLMs) using HuggingFace, LangChain, etc. Agentic AI : Experience with autonomous agents, LangChain Agents, AutoGPT, or similar agentic frameworks. Data Engineering : Ability to work with structured and unstructured data, data preprocessing, feature engineering, and pipeline creation. Soft Skills : Strong communication, collaboration, and problem-solving skills; ability to thrive in a fast-paced remote environment. Preferred Qualifications: Experience with RESTful APIs, Docker, and MLOps tools. Familiarity with generative AI tools and multimodal systems. Understanding of CI/CD for ML pipelines and model monitoring. Contributions to open-source AI/ML projects or published research. Why Join Us? Remote-first culture and flexible work hours Opportunity to work with the latest AI/ML technologies Challenging projects with global clients Competitive compensation and benefits Learning-centric environment with access to cloud credits, courses, and conferences Show more Show less

About Lowe’s Lowe’s Companies, Inc. (NYSE: LOW) is a FORTUNE® 50 home improvement company serving approximately 16 million customer transactions a week in the United States. With total fiscal year 2024 sales of more than $83 billion, Lowe’s operates over 1,700 home improvement stores and employs approximately 300,000 associates. Based in Mooresville, N.C., Lowe’s supports the communities it serves through programs focused on creating safe, affordable housing, improving community spaces, helping to develop the next generation of skilled trade experts and providing disaster relief to communities in need. For more information, visit Lowes.com. Job Summary The primary purpose of this role is to provide deep technical leadership in the development of cutting -edge data science, machine learning, and deep learning solutions to solve Lowe’s retail problems at massive scale. This position will provide a wide range of strategic and technical leadership, research, and production ready implementations and solutions collaborating closely with engineering, product management and business partner teams. You will support diverse areas of the home improvement retail business including, but not limited to: Supply Chain Data Science products like labor forecasting, Lane level forecasting, Dynamic service area modeling, Network flow modeling, Financial analytics and modeling , Inventory optimization across the network, Generative AI (LLM, Diffusion) and interactive chatbots to improve supply chain operations, safety, product data quality, and associate productivity across various distribution centers and for financial analysts. Roles & Responsibilities Core Responsibilities Effectively manage highly qualified team of data scientists (including director(s) and managers of DS teams) and motivate them to deliver impactful outcomes. Ability to deal with ambiguity, anticipate future business needs, implement strategic frameworks, and develop staff accordingly. Provides leadership to the team by attracting and hiring talented individuals, setting goals and communicating clear expectations, providing timely and constructive feedback as well as meaningful developmental opportunities, managing performance, providing resources and support as needed, and sponsoring and leading team members through change. Translates business challenges and opportunities into project ideas, manages data science projects, collaborates with engineering leadership for deploying models at scale, ultimately responsible for timely deliverables with high-quality. Builds, coaches, and mentors a strong team of Data Science professionals with varying levels of expertise. Build a strong set of next leaders for the organization. Collaborates with cross-functional groups, stakeholders, and leadership to ensure alignment and understand business needs and deliver actionable insights and AI enabled products to improve store operations, safety, product data quality, customer shopping experience, associate productivity across Lowes business. Maintain expert-level knowledge on industry trends, emerging technologies, managing research initiatives to explore their potential application in home improvement domain Partner with Product, Engineering, Business and Operations leadership to formulate roadmaps, influence decision making, and drive prioritization. Provides input for departmental budget and forecasting, and manages expenses associated with initiatives within scope of responsibility. Educational Qualifications Bachelor’s degree (Required): Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field (or equivalent work experience in a related field) Doctorate Degree (Preferred): Mathematics, Statistics, Physics, Economics, Engineering, Computer Science, Data or Information Science, or related quantitative analytic field Work Experience 15 years experience in applied advanced analytics (fewer years may be accepted with a Masters or Doctorate degree) 5 Years leadership experience with direct report responsibility 8 Years experience with advanced data modeling techniques 12 years’ experience in applied advanced analytics Primary Skills Data Science Modeling leveraging predictive and prescriptive techniques at Scale Large language Models Computer Vision models Responsible AI Data Drift and Bias Lowe's is an equal opportunity employer and administers all personnel practices without regard to race, color, religious creed, sex, gender, age, ancestry, national origin, mental or physical disability or medical condition, sexual orientation, gender identity or expression, marital status, military or veteran status, genetic information, or any other category protected under federal, state, or local law. Starting rate of pay may vary based on factors including, but not limited to, position offered, location, education, training, and/or experience. For information regarding our benefit programs and eligibility, please visit https://talent.lowes.com/us/en/benefits. Show more Show less

About Aviso AI: Aviso AI is revolutionizing enterprise sales intelligence with its cutting-edge AI solutions for forecasting, deal guidance, and revenue operations. By leveraging AI and machine learning, we transform how enterprise teams operate, allowing them to make data-driven decisions, optimize sales strategies, and increase productivity. Role Overview As a Senior Analyst, you will play a core role in uncovering insights from structured and unstructured data, evaluating model performance, and helping shape product and modeling decisions. This is a highly analytical role, focused on root cause analysis, pattern recognition, hypothesis testing, and strategic input into data-driven systems. You will work closely with data scientists, product managers, and business stakeholders to deliver clarity and direction from complex data landscapes. Key Responsibilities Conduct deep analyses of model predictions, surfacing accuracy issues, blind spots, and feature gaps. Partner with ML engineers to evaluate model drift, define success metrics, and assess performance over time. Perform root cause analysis on key business questions—such as forecast variances, deal slippage, or anomalies in pipeline behavior. Support the development of ground truth datasets and validate model outputs against business expectations. Collaborate with product and strategy teams to assess customer behavior, segment dynamics, and market patterns. Analyze interaction data (calls, emails, CRM updates) to identify patterns in successful deal progression. Contribute to experimentation efforts and comparative analysis of algorithmic improvements or new features. Present findings and recommendations clearly to technical and non-technical audiences. Qualifications 3 to 8 years of experience in analytics, data science, or strategy-oriented roles. Advanced SQL skills with experience working across large-scale relational datasets. Proficiency in Python (Pandas, NumPy, basic ML libraries) for data analysis and statistical exploration. Solid understanding of model evaluation metrics (e.g., AUC, precision/recall, F1, drift metrics). Experience working with messy, real-world data and turning it into reliable insight. Strong problem-solving and communication skills, with the ability to distill complex issues into actionable insights. Comfort operating independently in a fast-moving, cross-functional environment. Bonus: Prior experience with sales analytics, revenue forecasting, or working alongside ML/AI teams. Why Join Aviso AI? At Aviso AI, you’ll work in a collaborative environment alongside talented engineers, product managers, and data scientists. We’re committed to pushing the boundaries of AI and delivering industry-leading solutions that transform how enterprise sales teams operate. You’ll have the opportunity to work on exciting projects that apply advanced AI to real-world business problems and see the direct impact of your work. 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. EY-Consulting – AI Enabled Automation Developer– Senior We are looking to hire people with strong AI Enabled Automation skills and who are interested in applying AI in the process automation space – Azure, AI, ML, Deep Learning, NLP, GenAI , large Lang Models(LLM), RAG ,Vector DB , Graph DB, Python. 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. Responsibilities: Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Technical Skills Requirements 4 to 6 years of relevant professional experience Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. Strong foundation in ML algorithms, feature engineering, and model evaluation. Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP. Experience in GenAI technologies — LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI. Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Experience with multi-agent orchestration, memory, and tool integrations Experience/Implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning and reproducibility). Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. Good understanding of data pipelines, APIs, and distributed systems. Build observability into AI systems — latency, drift, performance metrics. Strong written and verbal communication, presentation, client service and technical writing skills in English for both technical and business audiences. Strong analytical, problem solving and critical thinking skills. Ability to work under tight timelines for multiple project deliveries. What we offer : At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. And while we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY you can be who you are and express your point of view, energy and enthusiasm, wherever you are in the world. It's how you make a difference. 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