Applied AI ML Researcher Lead

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

Lead an Applied AI Research team focused on building autonomous agent systems for financial services. The role involves architecting and delivering generative AI and agent-based solutions, establishing rigorous evaluation practices, and mentoring team members. Requires strong software engineering skills, experience with distributed computing, and a proven track record of deploying ML applications in production.

What you'd actually do

  1. Architect and deliver generative artificial intelligence and agent-based solutions that automate complex operational workflows end-to-end
  2. Translate priority business problems into research and engineering plans, success metrics, and scalable solution designs
  3. Build multi-agent systems that collaborate reliably, coordinate tasks, and improve over time through feedback and evaluation
  4. Design reusable services, libraries, and reference architectures that accelerate adoption across applied AI teams
  5. Establish rigorous experimentation practices, including offline/online evaluation, ablation testing, and error analysis, to drive measurable improvements

Skills

Required

  • Formal training or certification on applied artificial intelligence and machine learning concepts
  • 5+ years applied experience in AI/ML
  • Advanced degree (Master’s or Doctorate) in Computer Science, Machine Learning, Statistics, or a related quantitative field
  • Demonstrated experience designing experiments and evaluations for machine learning systems
  • Proven track record deploying machine learning applications into production environments
  • Strong software engineering skills in modern programming languages and machine learning frameworks
  • Experience building reusable components
  • Experience with distributed computing patterns for training and serving
  • Experience with state management for agent workflows
  • Ability to lead through influence across cross-functional teams

Nice to have

  • Experience building and evaluating autonomous agent systems (planning, tool-use, orchestration, and multi-agent coordination)
  • Experience with cloud-based machine learning platforms (AWS SageMaker, Amazon Bedrock)
  • Publications, open-source contributions, or other evidence of applied research impact
  • Familiarity with financial services domains and operational processes

What the JD emphasized

  • autonomous agents
  • agent-based solutions
  • multi-agent systems
  • applied AI teams
  • experimentation practices
  • offline/online evaluation
  • autonomous agent systems
  • applied research impact

Other signals

  • autonomous agents
  • multi-agent systems
  • enterprise-grade delivery
  • applied AI research