Applied AI/ML Lead: AI Agents & Production Systems

JPMorganChase; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health benefits

Equity incentives

Discretionary bonus

Job summary

JPMorganChase is seeking an Applied AI and Machine Learning Lead to drive the design and delivery of ML/ DL solutions across the AI and Data Platform team in Corporate Sector. You will own problem framing through productionization, building robust, scalable, measurable systems.

The role emphasizes mentorship, engineering discipline, and delivering machine learning solutions aligned with business goals. Collaboration with product, engineering, and data teams is essential.

Qualifications

• MS or PhD in Computer Science, ML, or a related field with at least 5 years of applied ML experience.
• Proficiency in Python; strong background in NLP and LLMs.
• Experience deploying ML models to production and collaborating with engineers.

Responsibilities

• Serve as a subject matter expert on a wide range of ML techniques and optimizations.
• Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
• Hands-on coding to bring experimental results into production solutions in Python; end-to-end ownership.
• Collaborate with product and engineering teams to deliver tailored, science-driven solutions.

Skills

Python

NLP & LLMs

PyTorch/TensorFlow

Distributed training

Leadership

Mentorship

Problem framing

Communication

Education

MS/PhD in CS/ML

Tools

Ray

MLFlow

SageMaker

AWS Cloud

Job description

JPMorganChase is seeking an Applied AI and Machine Learning Lead to drive the design and delivery of ML/ DL solutions across the AI and Data Platform team in Corporate Sector. You will own problem framing through productionization, building robust, scalable, measurable systems.

The role emphasizes mentorship, engineering discipline, and delivering machine learning solutions aligned with business goals. Collaboration with product, engineering, and data teams is essential.