1036 Mlflow Jobs - Page 35

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

FEQ226R103 As a Solutions Architect (Analytics, AI, Big Data, Public Cloud), you will guide the technical evaluation phase in a hands-on environment throughout the sales process. You will be a technical advisor internally to the sales team, and work with the product team as an advocate of your customers in the field. You will help our customers to achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. You'll grow as a leader in your field, while finding solutions to our customers ' biggest challenges in big data, analytics, data engineering and data science problems. The Impact You Will Have You will be a Big Data Analytics expert on aspects of architecture and design Lead your clients through evaluating and adopting Databricks including hands-on Apache Spark™ programming and integration with the wider cloud ecosystem Support your customers by authoring reference architectures, how-tos, and demo applications Integrate Databricks with 3rd-party applications to support customer architectures Engage with the technical community by leading workshops, seminars and meet-ups Together with your Account Executive, you will form successful relationships with clients throughout your assigned territory to provide technical and business value What We Look For Strong consulting / customer facing experience , working with external clients across a variety of industry markets Core strength in either data engineering or data science technologies 8+ years of experience demonstrating technical concepts, including demos, presenting and white-boarding 8+ years of experience designing architectures within a public cloud (AWS, Azure or GCP) 6+ years of experience with Big Data technologies, including Apache Spark™, AI, Data Science, Data Engineering, Hadoop, Cassandra, and others Coding experience in Python, R, Java, Apache Spark™ or Scala About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Show more Show less

Job Information Date Opened 05/28/2025 Job Type Full time Industry Education Work Experience 5+ years City S.A.S.Nagar (Mohali) State/Province Punjab Country India Zip/Postal Code 160062 Job Description About Data Couch Pvt. Ltd. Data Couch Pvt. Ltd. is a leading consulting and enterprise training company, specializing in Data Engineering, Big Data, Cloud Technologies, DevOps, and AI/ML. With a footprint across India and strategic global client partnerships, we empower organizations through data-driven decision-making and digital transformation. Our team of expert consultants and trainers works hands-on with the latest technologies to deliver enterprise-grade solutions and skill-building programs. Key Responsibilities Design, develop, and optimize scalable data pipelines using PySpark. Leverage Hadoop ecosystem tools (e.g., HDFS, Hive) for big data processing. Build and manage data workflows on cloud platforms (AWS, GCP, Azure). Utilize Kubernetes for orchestration of containerized data services. Collaborate with data scientists, analysts, and engineers to integrate data solutions. Monitor, maintain, and improve data workflows for performance and reliability. Ensure data governance, compliance, and best practices in documentation. Support MLOps and the integration of AI/ML pipelines into data workflows. Requirements Must-Haves: 6–7+ years of experience in data engineering roles. Strong expertise in PySpark for ETL, transformation, and distributed data processing. Hands-on experience with at least one major cloud platform (AWS, GCP, Azure). Solid understanding of Hadoop tools like HDFS, Hive, etc. Experience with Kubernetes for container orchestration. Proficient in Python and SQL. Experience working with large-scale, distributed data systems. Good-to-Have: Familiarity with tools like Apache Airflow, Kafka, NiFi, or Databricks. Experience with cloud data warehouses such as Snowflake, Redshift, or BigQuery. Exposure to MLOps frameworks such as MLflow, TensorFlow, or PyTorch. Understanding of DevOps, CI/CD, and version control (Git, GitLab, Jenkins). Benefits Innovative Environment: Thrive in a collaborative culture that values innovation and continuous improvement. Learning & Growth: Access to internal training programs, certifications, and mentorship from industry experts. Career Development: Structured growth opportunities and competitive compensation. Cutting-Edge Tech: Work with modern data technologies and contribute to digital transformation initiatives. Health & Wellbeing: Comprehensive medical insurance coverage for you. Work-Life Balance: Generous paid leave .

The AI, Data, and Analytics (AIDA) organization team, a Pfizer Digital organization, is responsible for the development and management of all data and analytics tools and platforms across the enterprise – from global product development, to manufacturing, to commercial, to point of patient care across over 100+ countries. One of the team’s top priorities is the development of Business Intelligence (BI), Reporting, and Visualization products which will serve as an enabler for the company’s digital transformation to bring innovative therapeutics to patients. Role Summary We are looking for a technically skilled and experienced Reporting Engineering, Senior Associate who is passionate about developing BI and data visualization products for our Customer Facing and Sales Enablement Colleagues, totaling over 20,000 individuals. This role involves working across multiple business segments globally to deliver top-tier BI Reporting and Visualization capabilities that enable impactful business decisions and high engagement user experiences. This role will work across multiple business segments globally to deliver best in class BI Reporting and Visualization capabilities that enable impactful business decisions and cohesive high engagement user experiences. In this position, you will be responsible for development of crucial business operations reports and dashboard products that drive company performance through continuously monitoring, measuring, identifying root cause, and proactively identifying patterns and triggers across the company to optimize performance. This role will also drive best practices and standards for BI & Visualization. This role will work closely with lead architect and lead engineers to develop reporting capabilities that elevate Customer Experience. This role requires working with complex and advanced data environments, employing the right architecture to build scalable semantic layers and contemporary reporting visualizations. The Reporting Senior Associate, will ensure data quality and integrity by validating the accuracy of KPIs and insights, resolving anomalies, implementing data quality checks, and conducting system integration testing (SIT) and user acceptance testing (UAT). The ideal candidate is a passionate and results-oriented product lead with a proven track record of delivering data and analytics driven solutions for the pharmaceutical industry. Role Responsibilities Engineering developer in business intelligence and data visualization products in service of field force and HQ enabling functions. Act as a Technical BI & Visualization developer on projects and collaborate with global team members (e.g. other engineers, regional delivery and activation teams, vendors) to architect, design and create BI & Visualization products at scale. Thorough understanding of data, business, and analytic requirements (incl. BI Product Blueprints such as SMART) to deliver high-impact, relevant data visualizations products while respecting project or program budgets and timelines. Deliver quality Functional Requirements and Solution Design, adhering to established standards and best practices. Follow Pfizer Process in Portfolio Management, Project Management, Product Management Playbook following Agile, Hybrid or Enterprise Solution Life Cycle. Extensive technical and implementation knowledge of multitude of BI and Visualization platforms not limiting to Tableau, MicroStrategy, Business Objects, MS-SSRS, and etc. Experience of cloud-based architectures, cloud analytics products / solutions, and data products / solutions (eg: AWS Redshift, MS SQL, Snowflake, Oracle, Teradata). Qualifications Bachelor’s degree in a technical area such as computer science, engineering, or management information science. Recent Healthcare Life Sciences (pharma preferred) and/or commercial/marketing data experience is highly preferred. Domain knowledge in the pharmaceutical industry preferred. Good knowledge of data governance and data cataloging best practices. 2+ years Relevant experience or knowledge in areas such as database management, data quality, master data management, metadata management, performance tuning, collaboration, and business process management. Strong Business Analysis acumen to meet or exceed business requirements following User Center Design (UCD). Working experience with testing of BI and Analytics applications – Unit Testing (e.g. Phased or Agile Sprints or MVP), System Integration Testing (SIT) and User Integration Testing (UAT). Experience with technical solution management tools such as JIRA or Github. Stay abreast of customer, industry, and technology trends with enterprise Business Intelligence (BI) and visualization tools. Technical Skillset 2+ years of hands-on experience in developing BI capabilities using Microstrategy Proficiency in common BI tools, such as Tableau, PowerBI, etc.. is a plus. Understand Dimensional Data Modelling principles (eg: Star Schema) Develop using Design System for Reporting as well as Adhoc Analytics Template Experience in working with cloud native SQL and NoSQL database platforms. Snowflake experience is desirable. Experience in AWS services EC2, EMR, RDS, Spark is preferred. Solid understanding of Scrum/Agile is preferred and working knowledge of CI/CD, GitHub MLflow. Familiarity with data privacy standards, governance principles, data protection, pharma industry practices/GDPR compliance is preferred. Great communication skills. Great business influencing and stakeholder management skills. Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates. Information & Business Tech Show more Show less

Role Summary The AI, Data, and Analytics (AIDA) organization team, a Pfizer Digital organization, is responsible for the development and management of all data and analytics tools and platforms across the enterprise – from global product development, to manufacturing, to commercial, to point of patient care across over 100+ countries. One of the team’s top priorities is the development of Business Intelligence (BI), Reporting, and Visualization products which will serve as an enabler for the company’s digital transformation to bring innovative therapeutics to patients. We are looking for a technically skilled and experienced Reporting Engineering Manager who is passionate about developing BI and data visualization products for our Customer Facing and Sales Enablement Colleagues, totaling over 20,000 individuals. This role involves working across multiple business segments globally to deliver top-tier BI Reporting and Visualization capabilities that enable impactful business decisions and high engagement user experiences. This role will work across multiple business segments globally to deliver best in class BI Reporting and Visualization capabilities that enable impactful business decisions and cohesive high engagement user experiences. In this position, you will be accountable to have a thorough understanding of data, business, and analytic requirements to deliver high-impact, relevant interactive data visualizations products that drive company performance through continuously monitoring, measuring, identifying root cause, and proactively identifying patterns and triggers across the company to optimize performance. This role will also drive best practices and standards for BI & Visualization. This role will work closely with stakeholders to understand their needs and ensure that reporting assets are created with a focus on Customer Experience. This role requires working with complex and advanced data environments, employing the right architecture to build scalable semantic layers and contemporary reporting visualizations. The Reporting Manager will ensure data quality and integrity by validating the accuracy of KPIs and insights, resolving anomalies, implementing data quality checks, and conducting system integration testing (SIT) and user acceptance testing (UAT). The ideal candidate is a passionate and results-oriented product lead with a proven track record of delivering data and analytics driven solutions for the pharmaceutical industry. Role Responsibilities Engineering expert in business intelligence and data visualization products in service of field force and HQ enabling functions. Act as a Technical BI & Visualization developer on projects and collaborate with global team members (e.g. other engineers, regional delivery and activation teams, vendors) to architect, design and create BI & Visualization products at scale. Thorough understanding of data, business, and analytic requirements (incl. BI Product Blueprints such as SMART) to deliver high-impact, relevant data visualizations products while respecting project or program budgets and timelines. Deliver quality Functional Requirements and Solution Design, adhering to established standards and best practices. Follow Pfizer Process in Portfolio Management, Project Management, Product Management Playbook following Agile, Hybrid or Enterprise Solution Life Cycle. Extensive technical and implementation knowledge of multitude of BI and Visualization platforms not limiting to Tableau, MicroStrategy, Business Objects, MS-SSRS, and etc. Experience of cloud-based architectures, cloud analytics products / solutions, and data products / solutions (eg: AWS Redshift, MS SQL, Snowflake, Oracle, Teradata). Qualifications Bachelor’s degree in a technical area such as computer science, engineering, or management information science. Recent Healthcare Life Sciences (pharma preferred) and/or commercial/marketing data experience is highly preferred. Domain knowledge in the pharmaceutical industry preferred. Good knowledge of data governance and data cataloging best practices. Relevant experience or knowledge in areas such as database management, data quality, master data management, metadata management, performance tuning, collaboration, and business process management. Strong Business Analysis acumen to meet or exceed business requirements following User Center Design (UCD). Strong Experience with testing of BI and Analytics applications – Unit Testing (e.g. Phased or Agile Sprints or MVP), System Integration Testing (SIT) and User Integration Testing (UAT). Experience with technical solution management tools such as JIRA or Github. Stay abreast of customer, industry, and technology trends with enterprise Business Intelligence (BI) and visualization tools. Technical Skillset 5+ years of hands-on experience in developing BI capabilities using Microstrategy Proficiency in common BI tools, such as Tableau, PowerBI, etc.. is a plus. Common Data Model (Logical & Physical), Conceptual Data Model validation to create Consumption Layer for Reporting (Dimensional Model, Semantic Layer, Direct Database Aggregates or OLAP Cubes) Develop using Design System for Reporting as well as Adhoc Analytics Template BI Product Scalability, Performance-tuning Platform Admin and Security, BI Platform tenant (licensing, capacity, vendor access, vulnerability testing) Experience in working with cloud native SQL and NoSQL database platforms. Snowflake experience is desirable. Experience in AWS services EC2, EMR, RDS, Spark is preferred. Solid understanding of Scrum/Agile is preferred and working knowledge of CI/CD, GitHub MLflow. Familiarity with data privacy standards, governance principles, data protection, pharma industry practices/GDPR compliance is preferred. Great communication skills. Great business influencing and stakeholder management skills. Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates. Information & Business Tech Show more Show less

The AI, Data, and Analytics (AIDA) organization team, a Pfizer Digital organization, is responsible for the development and management of all data and analytics tools and platforms across the enterprise – from global product development, to manufacturing, to commercial, to point of patient care across over 100+ countries. One of the team’s top priorities is the development of Business Intelligence (BI), Reporting, and Visualization products which will serve as an enabler for the company’s digital transformation to bring innovative therapeutics to patients. Role Summary We are looking for a technically skilled and experienced Reporting Engineering Senior Manager who is passionate about developing BI and data visualization products for our Customer Facing and Sales Enablement Colleagues, totaling over 20,000 individuals. This role involves working across multiple business segments globally to deliver top-tier BI Reporting and Visualization capabilities that enable impactful business decisions and high engagement user experiences. This role will work across multiple business segments globally to deliver best in class BI Reporting and Visualization capabilities that enable impactful business decisions and cohesive high engagement user experiences. In this position, you will be accountable to have a thorough understanding of data, business, and analytic requirements to deliver high-impact, relevant interactive data visualizations products that drive company performance through continuously monitoring, measuring, identifying root cause, and proactively identifying patterns and triggers across the company to optimize performance. This role will also drive best practices and standards for BI & Visualization. This role will work closely with stakeholders to understand their needs and ensure that reporting assets are created with a focus on Customer Experience. This role requires working with complex and advanced data environments, employing the right architecture to build scalable semantic layers and contemporary reporting visualizations. The Reporting Manager will ensure data quality and integrity by validating the accuracy of KPIs and insights, resolving anomalies, implementing data quality checks, and conducting system integration testing (SIT) and user acceptance testing (UAT). The ideal candidate is a passionate and results-oriented product lead with a proven track record of delivering data and analytics driven solutions for the pharmaceutical industry. Role Responsibilities Engineering expert in business intelligence and data visualization products in service of field force and HQ enabling functions. Act as a lead Technical BI & Visualization developer on projects and collaborate with global team members (e.g. other engineers, regional delivery and activation teams, vendors) to architect, design and create BI & Visualization products at scale. Responsible for BI solution architecture design and implementation. Thorough understanding of data, business, and analytic requirements (incl. BI Product Blueprints such as SMART) to deliver high-impact, relevant data visualizations products while respecting project or program budgets and timelines. Deliver quality Functional Requirements and Solution Design, adhering to established standards and best practices. Follow Pfizer Process in Portfolio Management, Project Management, Product Management Playbook following Agile, Hybrid or Enterprise Solution Life Cycle. Extensive technical and implementation knowledge of multitude of BI and Visualization platforms not limiting to Tableau, MicroStrategy, Business Objects, MS-SSRS, and etc. Experience of cloud-based architectures, cloud analytics products / solutions, and data products / solutions (eg: AWS Redshift, MS SQL, Snowflake, Oracle, Teradata). Qualifications Bachelor’s degree in a technical area such as computer science, engineering, or management information science. 9+ years Relevant experience or knowledge in areas such as database management, data quality, master data management, metadata management, performance tuning, collaboration, and business process management. Recent Healthcare Life Sciences (pharma preferred) and/or commercial/marketing data experience is highly preferred. Domain knowledge in the pharmaceutical industry preferred. Good knowledge of data governance and data cataloging best practices. Strong Business Analysis acumen to meet or exceed business requirements following User Center Design (UCD). Strong Experience with testing of BI and Analytics applications – Unit Testing (e.g. Phased or Agile Sprints or MVP), System Integration Testing (SIT) and User Integration Testing (UAT). Experience with technical solution management tools such as JIRA or Github. Stay abreast of customer, industry, and technology trends with enterprise Business Intelligence (BI) and visualization tools. Technical Skillset 9+ years of hands-on experience in developing BI capabilities using Microstrategy Proficiency in industry common BI tools, such as Tableau, PowerBI, etc. is a plus. Common Data Model (Logical & Physical), Conceptual Data Model validation to create Consumption Layer for Reporting (Dimensional Model, Semantic Layer, Direct Database Aggregates or OLAP Cubes) Develop using Design System for Reporting as well as Adhoc Analytics Template BI Product Scalability, Performance-tuning Platform Admin and Security, BI Platform tenant (licensing, capacity, vendor access, vulnerability testing) Experience in working with cloud native SQL and NoSQL database platforms. Snowflake experience is desirable. Experience in AWS services EC2, EMR, RDS, Spark is preferred. Solid understanding of Scrum/Agile is preferred and working knowledge of CI/CD, GitHub MLflow. Familiarity with data privacy standards, governance principles, data protection, pharma industry practices/GDPR compliance is preferred. Great communication skills. Great business influencing and stakeholder management skills. Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates. Information & Business Tech Show more Show less

The AI, Data, and Analytics (AIDA) organization team, a Pfizer Digital organization, is responsible for the development and management of all data and analytics tools and platforms across the enterprise – from global product development, to manufacturing, to commercial, to point of patient care across over 100+ countries. One of the team’s top priorities is the development of Business Intelligence (BI), Reporting, and Visualization products which will serve as an enabler for the company’s digital transformation to bring innovative therapeutics to patients. Role Summary We are looking for a technically skilled and experienced Reporting Engineering Senior Manager who is passionate about developing BI and data visualization products for our Customer Facing and Sales Enablement Colleagues, totaling over 20,000 individuals. This role involves working across multiple business segments globally to deliver top-tier BI Reporting and Visualization capabilities that enable impactful business decisions and high engagement user experiences. This role will work across multiple business segments globally to deliver best in class BI Reporting and Visualization capabilities that enable impactful business decisions and cohesive high engagement user experiences. In this position, you will be accountable to have a thorough understanding of data, business, and analytic requirements to deliver high-impact, relevant interactive data visualizations products that drive company performance through continuously monitoring, measuring, identifying root cause, and proactively identifying patterns and triggers across the company to optimize performance. This role will also drive best practices and standards for BI & Visualization. This role will work closely with stakeholders to understand their needs and ensure that reporting assets are created with a focus on Customer Experience. This role requires working with complex and advanced data environments, employing the right architecture to build scalable semantic layers and contemporary reporting visualizations. The Reporting Manager will ensure data quality and integrity by validating the accuracy of KPIs and insights, resolving anomalies, implementing data quality checks, and conducting system integration testing (SIT) and user acceptance testing (UAT). The ideal candidate is a passionate and results-oriented product lead with a proven track record of delivering data and analytics driven solutions for the pharmaceutical industry. Role Responsibilities Engineering expert in business intelligence and data visualization products in service of field force and HQ enabling functions. Act as a lead Technical BI & Visualization developer on projects and collaborate with global team members (e.g. other engineers, regional delivery and activation teams, vendors) to architect, design and create BI & Visualization products at scale. Responsible for BI solution architecture design and implementation. Thorough understanding of data, business, and analytic requirements (incl. BI Product Blueprints such as SMART) to deliver high-impact, relevant data visualizations products while respecting project or program budgets and timelines. Deliver quality Functional Requirements and Solution Design, adhering to established standards and best practices. Follow Pfizer Process in Portfolio Management, Project Management, Product Management Playbook following Agile, Hybrid or Enterprise Solution Life Cycle. Extensive technical and implementation knowledge of multitude of BI and Visualization platforms not limiting to Tableau, MicroStrategy, Business Objects, MS-SSRS, and etc. Experience of cloud-based architectures, cloud analytics products / solutions, and data products / solutions (eg: AWS Redshift, MS SQL, Snowflake, Oracle, Teradata). Qualifications Bachelor’s degree in a technical area such as computer science, engineering, or management information science. 9+ years Relevant experience or knowledge in areas such as database management, data quality, master data management, metadata management, performance tuning, collaboration, and business process management. Recent Healthcare Life Sciences (pharma preferred) and/or commercial/marketing data experience is highly preferred. Domain knowledge in the pharmaceutical industry preferred. Good knowledge of data governance and data cataloging best practices. Strong Business Analysis acumen to meet or exceed business requirements following User Center Design (UCD). Strong Experience with testing of BI and Analytics applications – Unit Testing (e.g. Phased or Agile Sprints or MVP), System Integration Testing (SIT) and User Integration Testing (UAT). Experience with technical solution management tools such as JIRA or Github. Stay abreast of customer, industry, and technology trends with enterprise Business Intelligence (BI) and visualization tools. Technical Skillset 9+ years of hands-on experience in developing BI capabilities using Microstrategy Proficiency in industry common BI tools, such as Tableau, PowerBI, etc. is a plus. Common Data Model (Logical & Physical), Conceptual Data Model validation to create Consumption Layer for Reporting (Dimensional Model, Semantic Layer, Direct Database Aggregates or OLAP Cubes) Develop using Design System for Reporting as well as Adhoc Analytics Template BI Product Scalability, Performance-tuning Platform Admin and Security, BI Platform tenant (licensing, capacity, vendor access, vulnerability testing) Experience in working with cloud native SQL and NoSQL database platforms. Snowflake experience is desirable. Experience in AWS services EC2, EMR, RDS, Spark is preferred. Solid understanding of Scrum/Agile is preferred and working knowledge of CI/CD, GitHub MLflow. Familiarity with data privacy standards, governance principles, data protection, pharma industry practices/GDPR compliance is preferred. Great communication skills. Great business influencing and stakeholder management skills. Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates. Information & Business Tech Show more Show less

Were seeking a Generative AI Engineer with 3-6 years of experience to design, develop, and deploy AI models that enhance our travel platforms. Youll work on LLMs, diffusion models, NLP, and other generative techniques to build solutions like dynamic content creation, conversational AI, and predictive travel recommendations. Skills & Qualifications 3-6 years of hands-on experience in AI/ML, with at least 1-2 years focused on generative AI. Proficiency in Python, PyTorch/TensorFlow, and frameworks like LangChain, Hugging Face, or LlamaIndex. Experience with LLM fine-tuning, prompt engineering, and RAG architectures. Knowledge of cloud platforms (AWS/GCP/Azure) and MLOps tools (MLflow, Kubeflow). Familiarity with travel industry data (e.g., booking systems, customer reviews) is a plus. Strong problem-solving skills and ability to translate business needs into AI solutions. Key Responsibilities Design, train, and fine-tune generative AI models (e.g., GPT, Llama, Stable Diffusion) for travel-specific use cases. Implement NLP pipelines for chatbots, personalized recommendations, and automated content generation. Optimize models for performance, scalability, and cost-efficiency (e.g., quantization, distillation). Collaborate with product teams to integrate AI into customer-facing applications (e.g., dynamic itineraries, virtual travel assistants). Stay ahead of industry trends (e.g., multimodal AI, RAG, autonomous agents) and prototype innovative solutions. Ensure ethical AI practices, bias mitigation, and compliance with data privacy regulations. Nice-to-Have Publications or projects in generative AI (GitHub, blogs, research papers). Experience with multimodal models (text + image/video generation). Exposure to graph neural networks (GNNs) for recommendation systems. What We Offer A fast-paced, collaborative, and growth-oriented environment. Direct impact on products used by millions of global travelers. Work on real-world AI challenges in a dynamic travel-tech environment. Competitive salary, and travel perks. Flexible work culture with a focus on innovation. Why Join Us ? At Thrillophilia, you will be part of a team that is dedicated to redefining the future of travel. We have millions of users, but to reach the next milestone, we need fresh perspectives and bold ideas to perfect every product and process. Here, you wont find the typical startup clichéstheres no excess, no fluff, just the raw, exhilarating challenge of creating the future of travel. At Thrillophilia, we dont just offer a job, we offer an experience! From Holis vibrant colors to Diwalis festive lights, every moment here is a celebration of life, energy, and creativity. We believe in empowering young minds to think big, innovate, and growbecause passion drives progress. Whether it's our grand festivals or recognizing and celebrating our top performers at the RnR, we make sure success never goes unnoticed. Forget the robotic 9-to-5; at Thrillophilia, we thrive on spontaneity, collaboration, and making every day feel like a grand event. (ref:hirist.tech) Show more Show less

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

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

Why MResult? Founded in 2004, MResult is a global digital solutions partner trusted by leading Fortune 500 companies in industries such as pharma & healthcare, retail, and BFSI. MResult’s expertise in data and analytics, data engineering, machine learning, AI, and automation help companies streamline operations and unlock business value. As part of our team, you will collaborate with top minds in the industry to deliver cutting-edge solutions that solve real-world challenges. What We Offer: At MResult, you can leave your mark on projects at the world’s most recognized brands, access opportunities to grow and upskill, and do your best work with the flexibility of hybrid work models. Great work is rewarded, and leaders are nurtured from within. Our values — Agility, Collaboration, Client Focus, Innovation, and Integrity — are woven into our culture, guiding every decision. What This Role Requires In the role of Data Engineer, you will be a key contributor to MResult’s mission of empowering our clients with data-driven insights and innovative digital solutions. Each day brings exciting challenges and growth opportunities. Here is what you will do: • Project solutioning, including scoping, and estimation. • Data sourcing, investigation, and profiling. • Prototyping and design thinking. • Developing data pipelines & complex data workflows. • Actively contribute to project documentation and playbook, including but not limited to physical models, conceptual models, data dictionaries and data cataloguing. Key Skills to Succeed in This Role: • Overall 8+ years of experience, 4+ years of hands-on experience in working with Python in building data pipelines and processes. • Proficiency in SQL programming, including the ability to create and debug stored procedures, functions, and views. • 4+ years of hands-on experience delivering data lake/data warehousing projects. Driving Innovation, Empowering Insights • Experience in working with cloud native SQL and NoSQL database platforms. Snowflake experience is desirable. • Experience in AWS services EC2, EMR, RDS, Spark is preferred. • Solid understanding of Scrum/Agile is preferred and working knowledge of CI/CD,GitHub MLflow Manage, Master, and Maximize with MResult MResult is an equal-opportunity employer committed to building an inclusive environment free of discrimination and harassment. Take the next step in your career with MResult — where your ideas help shape the future. Thanks & Regards, Surendra Singh Show more Show less

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

Job Description: We are seeking a skilled and innovative AI/ML Engineer to design, build, and deploy machine learning solutions that solve complex business challenges in mission-critical industries. You will work with multidisciplinary teams to apply AI, ML, and deep learning techniques to large-scale datasets and real-time operational systems. Key Responsibilities: Design and implement end-to-end ML pipelines: data ingestion, model training, evaluation, and deployment Build predictive and prescriptive models using structured, unstructured, and real-time data Develop and fine-tune deep learning models for NLP, computer vision, or time series forecasting Integrate ML models into enterprise platforms, APIs, and dashboards Work closely with domain experts, data engineers, and DevOps teams to ensure production-grade performance Conduct model validation, bias testing, and post-deployment monitoring Document workflows, architecture, and results for reproducibility and audits Research and evaluate new AI tools, techniques, and trends Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or related field 5-7 years of hands-on experience in developing and deploying ML models Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost) Experience with NLP (BERT, spaCy) or CV frameworks (OpenCV, YOLO, MMDetection) Familiarity with data processing tools (Pandas, Dask, Apache Spark) Proficient in SQL and experience with time-series or sensor data Knowledge of ML Ops practices and tools (Docker, MLflow, Airflow, Kubernetes) Industry experience in Oil & Gas, Power Systems, or Urban Analytics Hands-on with edge AI (Jetson, Coral), GPU compute, and model optimization Cloud services: AWS SageMaker, Azure ML, or Google AI Platform Familiarity with REST APIs, OPC-UA integration, or SCADA data sources Knowledge of responsible AI practices (explainability, fairness, privacy).

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

We are looking for a ML Ops Engineer to join our Technology team at Clarivate. You will get the opportunity to work in a cross-cultural work environment while working on the latest web technologies with an emphasis on user-centered design. About You (Skills & Experience Required) Bachelor’s or master’s degree in computer science, Engineering, or a related field. 5+ years of experience in machine learning, data engineering, or software development. Good experience in building data pipelines, data cleaning, and feature engineering is essential for preparing data for model training. Knowledge of programming languages (Python, R), and version control systems (Git) is necessary for building and maintaining MLOps pipelines. Experience with MLOps-specific tools and platforms (e.g., Kubeflow, MLflow, Airflow) can streamline MLOps workflows. DevOps principles, including CI/CD pipelines, infrastructure as code (IaaC), and monitoring is helpful for automating ML workflows. Experience with atleast one of the cloud platforms (AWS, GCP, Azure) and their associated services (e.g., compute, storage, ML platforms) is essential for deploying and scaling ML models. Familiarity with container orchestration tools like Kubernetes can help manage and scale ML workloads efficiently. It would be great if you also had, Experience with big data technologies (Hadoop, Spark). Knowledge of data governance and security practices. Familiarity with DevOps practices and tools. What will you be doing in this role? Model Deployment & Monitoring Oversee the deployment of machine learning models into production environments. Ensure continuous monitoring and performance tuning of deployed models. Implement robust CI/CD pipelines for model updates and rollbacks. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Communicate project status, risks, and opportunities to stakeholders. Provide technical guidance and support to team members. Infrastructure & Automation Design and manage scalable infrastructure for model training and deployment. Automate repetitive tasks to improve efficiency and reduce errors. Ensure the infrastructure meets security and compliance standards. Innovation & Improvement Stay updated with the latest trends and technologies in MLOps. Identify opportunities for process improvements and implement them. Drive innovation within the team to enhance the MLOps capabilities. About The Team You would be part of our incredible data science team of Intellectual property (IP) group & work closely with product and technology teams spreads across various locations worldwide. You would be working on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services. Hours of Work This is a permanent position with Clarivate.9 hours per day including lunch break. you should be flexible with working hours to align with globally distributed teams and stakeholders. At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations. Show more Show less

Walk-in interview only -BLR No virtual Python & libraries scikit-learn, TensorFlow,PyTorch/XGBoost exp in supervised, unsupervised, and deep learning techniques Deployment tools Flask, FastAPI, Docker AWS GCP, Azure &ML,SQL Contact Maya 9880516218

Job Summary: We are looking for a skilled and innovative Machine Learning Engineer to develop, implement, and optimize intelligent systems that leverage data to drive business decisions and enhance product functionality. The ideal candidate will have strong programming skills, a solid understanding of machine learning algorithms, and experience in deploying models into production environments. Key Responsibilities: Design and develop scalable ML models and algorithms to solve real-world problems Analyze large and complex datasets to extract actionable insights Train, test, and validate models to ensure performance and accuracy Work closely with data engineers, product teams, and stakeholders to integrate ML models into applications Research and stay updated on state-of-the-art techniques in machine learning and AI Optimize models for speed, scalability, and interpretability Document processes, experiments, and results clearly Deploy models into production using MLOps tools and practices Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or related field Strong proficiency in Python and ML libraries like scikit-learn, TensorFlow, PyTorch, Keras Solid understanding of statistical modeling, classification, regression, clustering, and deep learning Experience with data handling tools (e.g., Pandas , NumPy ) and data visualization (e.g., Matplotlib , Seaborn ) Proficiency with SQL and working knowledge of big data technologies (e.g., Spark, Hadoop) Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools (e.g., MLflow, SageMaker) Preferred Qualifications: Experience with NLP, computer vision, or recommendation systems Knowledge of Docker, Kubernetes, and CI/CD for model deployment Published research or contributions to open-source ML projects Exposure to agile environments and collaborative workflows Show more Show less

CSQ326R28 The Machine Learning (ML) Practice team is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. The Impact You Will Have Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation Build, scale, and optimize customer data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains Advise data teams on various data science such as architecture, tooling, and best practices Present at conferences such as Data+AI Summit Provide technical mentorship to the larger ML SME community in Databricks Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap What We Look For Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI 4+ years of hands-on industry data science experience, leveraging machine learning and data science tools including pandas, scikit-learn, gensim, nltk, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration, life-long learning, and driving business value through ML About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Show more Show less