Applied AI ML Researcher Director

JPMorgan Chase JPMorgan Chase · Banking · Palo Alto, CA +1 · Commercial & Investment Bank

Lead the development and deployment of next-generation autonomous AI agents for a financial institution, focusing on automating complex operations and scaling solutions across the organization. This role involves architecting GenAI solutions, mentoring teams, and ensuring production-readiness.

What you'd actually do

  1. Architect and develop GenAI and agentic solutions to automate complex operational processes
  2. Assist Lines of Business and teams to directly solve priority use cases within the domain
  3. Deliver multiple agents that collaborate to solve large, complex problems, orchestrate end-to-end workflows, and scale across JPMC
  4. Design and build services and libraries that AI teams want to use
  5. Mentor and inspire a team of AI engineers, fostering a culture of excellence, innovation, and continuous learning

Skills

Required

  • PhD in Computer Science or a related quantitative discipline with 8+ years of relevant experience or MS in Computer Science or a related field with 12+ years of relevant experience
  • Research experience or work in a top commercial AI research lab
  • Deep understanding of AI fundamentals and practical experience with data analysis and experimental design
  • Proven track record of deploying AI/ML applications in a production environment at scale
  • Familiarity with distributed computing patterns for training, serving, and persistence of state
  • Experience integrating user feedback to establish agentic refinement and self-improving AI applications
  • Experience in building and leading high-performing AI teams

Nice to have

  • Experience deploying models on AWS platforms such as SageMaker or Bedrock

What the JD emphasized

  • architects who will define the future of banking through Agentic AI
  • agentic AI
  • frontier models
  • architect and develop GenAI and agentic solutions
  • Deliver multiple agents that collaborate to solve large, complex problems, orchestrate end-to-end workflows, and scale across JPMC
  • AI teams want to use
  • AI engineers
  • AI/ML applications in a production environment at scale
  • distributed computing patterns for training, serving, and persistence of state
  • agentic refinement and self-improving AI applications
  • building and leading high-performing AI teams

Other signals

  • autonomous agents
  • agentic AI
  • frontier models
  • large-scale
  • deployable systems