Applied AI ML Lead, Chief Data & Analytics Office

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 280,000; Full time

Job summary

JPMorgan Chase & Co. seeks an Applied AI ML Lead to head development and deployment of innovative AI solutions within the Chief Data & Analytics Office.

You will guide cross‑functional teams to tackle complex business challenges, drive modern ML practices, and ensure governance and responsible AI standards. You will own end-to-end Python development for proof‑of‑concept and production systems, collaborating with product, engineering, and business stakeholders to deliver scalable AI that adds

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, large language models, or foundation models.
• At least 5 years of experience programming in Python; experience with ML frameworks such as PyTorch or TensorFlow.
• 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).
• Strong communication skills with the ability to explain complex technical concepts to diverse audiences.
• Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.
• Experience applying data science and ML techniques to solve business problems.
• Passion for detail, follow-through, and technical excellence.

Responsibilities

• Lead hands-on design, development, and deployment of AI, GenAI, and large language model solutions.
• Serve as a subject matter expert on a wide range of machine learning techniques and optimizations.
• Collaborate with product, engineering, and business teams to deliver scalable, production-ready AI systems.
• Conduct experiments using the latest ML technologies, analyze results, and tune models for optimal performance.
• Own end-to-end code development in Python for both proof-of-concept and production-ready solutions.
• Integrate generative AI within the ML platform using state-of-the-art techniques.
• Drive adoption of modern ML infrastructure, tools, and best practices.
• Optimizes system accuracy and performance by identifying and resolving inefficiencies.
• Communicate technical concepts and results to both technical and business stakeholders.
• Ensure responsible AI practices, model governance, and compliance with regulatory standards.
• Mentor and guide other AI engineers and scientists, fostering a culture of continuous learning.

Skills

Python

PyTorch

TensorFlow

ML workflows

MLOps

Cloud AWS

Kubernetes

Ray

CI/CD for ML

Communication

Leadership

Regulatory governance

Education

Master’s degree

PhD

Tools

MLflow

Ray

Slurm

NVIDIA DCGM

Job description

Join a world-class data science team at JPMorgan Chase and help shape the future of our Chief Administrative Office. As a leader in applied AI and machine learning,you’llhave the opportunity to work on high-impact projects that influence the way we do business across multiple domains. Collaborate with talented colleagues,leveragecutting-edgetechnologies, and see your work make a tangible difference. We value curiosity, technical excellence, and a passion for solving complex problems. Ifyou’reready to accelerate your career and drive meaningful change, we want to hear from you.

As an Applied AI ML Lead in the Chief Data & Analytics Office, you will lead the development and deployment of innovative AI and machine learning solutions. You will collaborate with cross-functional teams to address complex business challenges, drive adoption of modern ML practices, and ensure responsible AI governance. You will have the opportunity to work with state-of-the-art technologies and contribute to a culture of technical excellence and continuous learning.

Job Responsibilities:

• Lead the hands-on design, development, and deployment of advanced AI, GenAI, and large language model solutions.
• Serve as a subject matter expert on a wide range of machine learning techniques and optimizations.
• Collaborate with product, engineering, and business teams to deliver scalable, production-ready AI systems.
• Conduct experiments using the latest ML technologies, analyze results, and tune models for optimalperformance.
• Own end-to-end code development in Python for both proof-of-concept and production-ready solutions.
• Integrate generative AI within the ML platform using state-of-the-art techniques.
• Drive adoption of modern ML infrastructure, tools, and best practices.
• Optimizesystem accuracy and performance by identifying and resolving inefficiencies.
• Communicate technical concepts and results to both technical and business stakeholders.
• Ensure responsible AI practices, model governance, and compliance with regulatory standards.
• Mentor and guide other AI engineers and scientists, fostering a culture of continuous learning.

Required Qualifications, Capabilities, and Skills:

• 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, large language models, or foundation models.
• At least 5 years of experience programming in Python; experience with ML frameworks such as PyTorch or TensorFlow.
• 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).
• Strong communication skills with the ability to explain complex technical concepts to diverse audiences.
• Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.
• Experience applying data science and ML techniques to solve business problems.
• Passion for detail, follow-through, and technical excellence.

Preferred Qualifications, Capabilities, and Skills:

• Experience with high-performance computing and GPU infrastructure (e.g., NVIDIA DCGM, Triton Inference).
• Familiarity with big data processing tools and cloud data services.
• Advanced knowledge in reinforcement learning, meta learning, or related advanced ML areas.
• Experience with search/ranking, recommender systems, or graph techniques.
• Background in financial services or regulated industries.
• Experience with building and deploying ML models on cloud platforms such as AWS Sagemaker, EKS, etc.
• Published research or contributions to open-source GenAI/LLM projects.

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