Applied AI ML Engineer Lead

Our goal is to build the next generation of AI: autonomous agents that can reason, plan, act, and learn to solve critical problems for an industry leading financial institution. We are looking for architects who will define the future of banking through Agentic AI.  The Applied Artificial Intelligence and Machine Learning team in Commercial and Investment Banking is transforming operations by leveraging the latest advancements in agentic AI and frontier models.  As an Applied Artificial Intelligence and Machine Learning Lead at JPMorgan

Chase within the Applied AI Research team in Commercial and Investment Banking, you will help build autonomous agent systems that can reason, plan, act, and learn to solve high-impact business problems. You will bridge cutting-edge research and enterprise-grade delivery, shaping how applied AI is designed, evaluated, and deployed  will partner closely with business and technology stakeholders to translate priority needs into measurable outcomes, while raising engineering and scientific standards across the team.

Job Responsibilities Architect and deliver generative artificial intelligence and agent-based solutions that automate complex operational workflows end-to-end Translate priority business problems into research and engineering plans, success metrics, and scalable solution designs

Build multi-agent systems that collaborate reliably, coordinate tasks, and improve over time through feedback and evaluation

Design reusable services, libraries, and reference architectures that accelerate adoption across applied AI teams

Establish rigorous experimentation practices, including offline/online evaluation, ablation testing, and error analysis, to drive measurable improvements

Mentor and develop applied AI engineers and researchers, fostering a culture of scientific rigor, ownership, and continuous learning

Partner with stakeholders across business and technology teams to scale solutions responsibly, balancing performance, reliability, and security

Required Qualifications , Capabilities, and Skills Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience

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, including clear metrics and reproducible results

Proven track record deploying machine learning applications into production environments with operational excellence (monitoring, reliability, and lifecycle management)
Strong software engineering skills in modern programming languages and machine learning frameworks, with experience building reusable components

Experience with distributed computing patterns for training and serving, and with state management for agent workflows

Ability to lead through influence across cross-functional teams, translating complex technical topics for varied audiences

Preferred Qualifications , Capabilities, and Skills Experience building and evaluating autonomous agent systems (planning, tool-use, orchestration, and multi-agent coordination)

Experience with cloud-based machine learning platforms, such as Amazon Web Services (AWS) Sage Maker or Amazon Bedrock Publications, open-source contributions, or other evidence of applied research impact in machine learning or generative artificial intelligence

Familiarity with financial services domains and operational processes, including risk-aware design and production constraintsFEDERAL DEPOSIT INSURANCE ACT:
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan

Chase’s…