Applied Artificial Intelligence/ Machine Learning Lead - Vice President

JPMorgan Chase & Co.
Wilmington, DE, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$171,000.0 - $260,000.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Continuous Integration Graph Database Information Retrieval Python (Programming Language) Machine Learning Natural Language Processing Recommender Systems Tensorflow Software Engineering Reinforcement Learning
+10 more
Pytorch Ontology Design Retrieval-Augmented Generation Large Language Models Agentic-AI Build Management Integration Tests Entity Resolution Artificial Intelligence Markup Language (AIML) Human in the Loop

Job description

As an Applied AI/ML Vice President within Global Private Bank, you will lead the design and build of agentic AI systems that execute reliable business workflows end-to-end. You will bring deep expertise in agent architectures-including memory, state, and context management; loop engineering; tool orchestration; and spec-driven development-to deliver safe, observable, and high-quality solutions. You will stay close to cutting-edge research, translating advances in LLMs, agent frameworks, reinforcement learning, knowledge graphs, retrieval, and self-improving systems into practical capabilities. You’ll thrive in a highly collaborative environment, partnering with business, technologists, and control partners to shape requirements, controls, and success metrics.., * Develop advanced agentic AI solutions across NLP, speech analytics, time series, reinforcement learning, and recommendation systems.

  • Design robust agent architectures combining LLM reasoning with tools, structured data, and APIs-spanning state, memory, and context management, plus loop engineering (plan/act/observe, verification, termination, and fallback/escalation).
  • Engineer reliable agent-driven workflows emphasizing correctness, traceability, and control-aware behavior (guardrails, approvals, auditable decision paths).
  • Build knowledge-centric reasoning layers, including knowledge graphs and hybrid retrieval (RAG + graph + structured sources) to improve grounding and accuracy.
  • Drive specification-driven development: author specs and contracts (schemas, validators, tool/skill interfaces) and build evaluation/regression harnesses.
  • Advance agent quality via recursive self-improvement through automated evaluation and critique loops, red-team feedback, skill/prompt instruction optimization, and outcome-driven dataset curation (human-in-the-loop as needed).
  • Coach and mentor AIML team members, setting a high bar for engineering rigor and research depth.

Requirements

  • PhD in a quantitative discipline (e.g., CS/EE/Math/OR/Optimization/Data Science) or equivalent industry/research experience (e.g., 3+ years with PhD-equivalent depth; or MS with 5+ years).
  • Demonstrated expertise building agentic AI systems, including several of: memory/state/context management, tool orchestration and workflow reliability patterns, loop engineering, spec-driven development, and prompt/skill instruction optimization.
  • Strong hands-on experience with ML/DL methods and toolkits (e.g., PyTorch/TensorFlow plus core Python data/ML stack).
  • Ability to design experiments and evaluation frameworks with metrics aligned to business outcomes (quality, reliability, latency, cost, safety).
  • Experience with scalable data and model workflows (training and/or inference) and strong software engineering practices.
  • strong communication skills to explain technical concepts to both technical and business audiences.

Preferred qualifications, capabilities, and skills:

  • Knowledge in search/ranking, reinforcement learning, or meta-learning (especially for agent routing, policies, and self-improvement).
  • Experience with knowledge graphs, entity resolution, and ontology design.
  • Experience with A/B experimentation and metric-driven product development; CI pipelines and unit/integration testing.

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

About the company

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management., J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

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