Applied AI ML Lead

Testing Site - JPMC; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase in Jersey City, NJ, seeks an Applied AI ML Lead to steer the development and deployment of innovative AI and ML solutions. You will collaborate with cross-functional teams to address complex business challenges, promote modern ML practices, and ensure responsible AI governance.

You will mentor engineers, drive adoption of ML infrastructure, and lead end-to-end Python development for production-ready systems. This role emphasizes technical excellence and cross-domain impact.

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 communications 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 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 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.
• Optimize 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

GenAI

LLMs

PyTorch

TensorFlow

Cloud Platforms

Kubernetes

Ray

MLOps

Leadership

Communication

Education

Master's or PhD in CS/Engineering/Math

Tools

PyTorch

TensorFlow

Kubernetes

Ray

MLflow

CI/CD for ML

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-arttechnologies 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 foroptimalperformance.
• Own end-to-end code development in Python for both proof-of-concept and production-ready solutions.
• Integrate generative AI within the ML platform usingstate-of-the-arttechniques.
• Drive adoption of modern ML infrastructure, tools, and best practices.
• Optimizesystem accuracy and performance byidentifyingand 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 asPyTorchor 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 ofMLOpstools and practices (MLflow, model monitoring, CI/CD for ML).
• Strong communicationskills 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 withbuilding and deploying ML models on cloud platforms such as AWSSagemaker, EKS, etc.
• Published research or contributions to open-source GenAI/LLM projects.

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