Data Scientist Lead - Applied AI ML
at J.P. Morgan
Posted 16 days ago
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As a Lead Data Scientist in the Chief Data Office you'll shape and deliver GenAI, LLM, and agentic AI solutions for the firm's administrative businesses. You will lead hands-on development, provide technical direction, and collaborate with cross-functional teams to build scalable, production-ready ML systems and drive MLOps adoption. The role includes communicating technical concepts to both technical and business stakeholders and ensuring responsible AI practices and model governance.
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Location: Bengaluru, Karnataka, India
As a Lead Data Scientist with the Chief Data Office, you’ll help shape the future of the Chief Administrative Office and its businesses by applying world-class machine learning expertise. You’ll collaborate on a wide array of product and business problems with cross-functional partners across Finance, Supplier Services, Data Security, Global Real Estate, and Customer Experience. You’ll use data and analysis to identify and solve our division’s biggest challenges and develop state-of-the-art GenAI and LLM models to solve real-world problems. By joining JP Morgan Chief Data Office (CAO), you’ll be part of a world-class data science community dedicated to problem solving and career growth in ML/AI and beyond.
Job Summary
- Lead hands-on development and technical direction for GenAI, LLM, and agentic AI solutions.
- Collaborate with cross-functional teams to deliver scalable, production-ready AI systems.
- Drive adoption of modern ML infrastructure and best practices.
- Communicate technical concepts and results to both technical and business stakeholders.
- Ensure responsible AI practices and model governance.
Job Responsibilities
- Master’s or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field.
- 10+ years of hands-on experience in applied machine learning, including GenAI, LLMs, or foundation models.
- Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX).
- Proven experience designing, training, and deploying large-scale ML/AI models in production environments.
- Deep understanding of prompt engineering, agentic workflows, and orchestration frameworks.
- Experience with cloud platforms (AWS, Azure, GCP) and distributed systems (Kubernetes, Ray, Slurm).
- Solid grasp of MLOps tools and practices (MLflow, model monitoring, CI/CD for ML).
- Ability to communicate complex technical concepts to both technical and business stakeholders
Preferred Qualifications
- Experience with high-performance computing and GPU infrastructure (NVIDIA DCGM, Triton Inference).
- Familiarity with big data processing tools and cloud data services.
- Background in financial services or regulated industries.
- Published research or contributions to open-source GenAI/LLM projects.
Drive innovation by building advanced AI and machine learning products for real-world problem solving
