Applied AI ML Lead Researcher - Commercial and Investment Bank
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-10-18
Listing for:
Testing Site - JPMC
Full Time
position Listed on 2026-10-18
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
Our goal is to build the next generation of AI: autonomous agents that can reason, plan,actand learnto solve criticalproblemsfor an industry leading financial institution. Weare looking for architects who will definethe future of banking through Agentic AI.The Applied Artificial Intelligence and Machine Learning team in Commercial and Investment Banking is transformingoperationsbyleveragingthe latest advancements inagentic AI and frontier models.
As an Applied AI ML Lead Researcher in the Applied AI Research team you will be a builder, a scientific pioneer and mentor who bridges the gap between leading edge theory and enterprise-grade,large-scale,deployable systems.
Job Responsibilities:- Architect and develop GenAI and agentic solutions to automate complex operational processes
- Assist Lines of Business and teams to directly solve priority use cases within the domain
- Deliver multiple agents that collaborate to solve large, complex problems, orchestrate end-to-end workflows, and scale across JPMC
- Design and build services and libraries that AI teams want to use
- Mentor and inspire a team of AI engineers, fostering a culture of excellence, innovation, and continuous learning
- Ensure the scalability, reliability, and security of AI/ML solutions in a production environment, with a focus on long-term sustainability
- Collaborate with stakeholders and technical partners across Lines of Business and firmwide to scale solutions and maximize impact
Skills:
- 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
Skills:
- Experience deploying models on AWS platforms such as Sage Maker or Bedrock will be strongly considered, but not required
- PhD level education
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