Applied AI ML Lead Engineer

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'll have the opportunity to work on high-impact projects that influence the way we do business across multiple domains.

Collaborate with talented colleagues, leverage cutting-edge technologies, and see your work make a tangible difference.

We value curiosity, technical excellence, and a passion for solving complex problems.

If you're ready to accelerate your career and drive meaningful change, we want to hear from you.

Job Summary:
As a Applied AI ML VP 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 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.

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 ...