VP, Applied AI & ML Engineering - Autonomous Systems
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Role details
Tech stack
Job description
deliver production architectures for AI-powered products and services, working at the intersection of software engineering and scientific research to translate innovative ideas into scalable enterprise solutions. You will collaborate with cloud and SRE teams in a role that offers flexibility for individual contributors and optional management responsibilities, depending on your interests and experience. You will help shape the team culture and drive impactful change.Job Responsibilities:Design and deliver enterprise-grade machine learning systemsCollaborate with cloud and SRE teams to build robust production architecturesTranslate scientific research into scalable ML solutionsDevelop and deploy business-critical, data-intensive applicationsImplement distributed, multi-threaded, and scalable applicationsBuild, test, and deploy automated pipelines for ML solutionsLeverage foundational libraries and services for re-use across teamsApply best practices in software engineering and computer
Requirements
scienceUtilize MLOps tools for versioning, reproducibility, and observabilityAlign ML problem definitions with business objectivesMentor and support team members, with optional management responsibilitiesRequired Qualifications, Capabilities, and Skills:Experience in machine learning engineering rolesDegree in a quantitative discipline (Computer Science, Mathematics, Statistics)Proven ability to develop and deploy business-critical, data-intensive applicationsExtensive experience with AWS and KubernetesProficiency with lower-level libraries such as PyTorch and NumPyHands-on experience implementing distributed, multi-threaded, and scalable applicationsExperience with automated building, testing, and deployment pipelinesFamiliarity with higher-level interfaces like Pydantic AI and LangraphStrong understanding of computer science fundamentals and development best practicesBroad knowledge of MLOps tooling for versioning, reproducibility, and observabilityAbility to understand business objectives and align ML problem definitionsPreferred Qualifications, Capabilities, and Skills:Experience mentoring or leading teamsKnowledge of agentic AI conceptsExperience designing reusable libraries and servicesInterest in bridging scientific theory and enterprise-grade systemsPassion for innovation and continuous learningWhy Join Us? You will be part of a pioneering team that is transforming banking with AI. We offer opportunities for career growth, mentorship, and the chance to work on impactful projects that shape the industry. Your expertise will help us build the next generation of AI solutions, making a difference for our clients and communities worldwide. #J-18808-Ljbffr
About the company
Join us in shaping the future of AI at JPMorganChase, where you can make a real impact by building autonomous agents that solve critical challenges. We value your expertise and encourage you to pioneer new approaches, bridging theory and practice while collaborating with talented teams across the globe to help define how AI transforms the world’s largest bank. Experience career growth, mentorship, and the excitement of building next-generation solutions.We’re developing an AI platform and desktop application that helps users automate their document processing workflows at the world’s biggest bank, already operating at hundreds of documents per second and doubling every three months, leveraging agentic systems that are powerful, truly generalizable, and scalable while maintaining security in a highly sensitive enterprise environment.As a Machine Learning Engineer in the Applied Artificial Intelligence and Machine Learning team within Commercial & Investment Banking, you will design and
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