Applied AI ML Lead for GenAI & Production ML

Aumni; Jersey City (NJ); On-site; USD 230,000 - 340,000; Full time

Benefits offered by this job

Health care coverage

Retirement plan

Tuition reimbursement

Job summary

JPMorgan Chase is seeking an Applied AI ML Lead to drive development and deployment of state-of-the-art AI and machine learning solutions within the Chief Data & Analytics Office. You will mentor engineers, collaborate with product and engineering teams, and promote responsible AI governance across the organization.

The role emphasizes hands-on development in Python, end-to-end ML lifecycle ownership, and leading initiatives that scale across multiple business domains.

Qualifications

• Master’s or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field.
• Minimum 8 years of hands-on experience in applied machine learning, including generative AI, LLMs, or foundation models.
• At least 5 years of Python programming; experience with PyTorch or TensorFlow.
• Proven experience designing, training, and deploying large-scale ML/AI models in production.

Responsibilities

• Lead hands-on design, development, and deployment of advanced AI, GenAI, and LLM solutions.
• Serve as SME on a wide range of ML techniques and optimizations.
• Collaborate with product, engineering, and business teams for scalable AI systems.
• Conduct experiments, analyze results, and tune models for performance.
• Own end-to-end code development in Python for proofs-of-concept and production.

Skills

Python

PyTorch/TensorFlow

ML deployment

Cloud platforms

Kubernetes/Ray

MLOps

Leadership

Communication

Prompt engineering

Education

Master’s or PhD in CS/Engineering/Math

Tools

MLflow

CI/CD for ML

Kubernetes

Ray

Slurm

Job description

JPMorgan Chase is seeking an Applied AI ML Lead to drive development and deployment of state-of-the-art AI and machine learning solutions within the Chief Data & Analytics Office. You will mentor engineers, collaborate with product and engineering teams, and promote responsible AI governance across the organization.

The role emphasizes hands-on development in Python, end-to-end ML lifecycle ownership, and leading initiatives that scale across multiple business domains.