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# Applied Artificial Intelligence/ Machine Learning Lead - Vice President

- **Company:** JPMorgan Chase & Co.
- **Location:** Jersey City, NJ, United States
- **Experience:** Expert
- **Salary:** $171,000.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Continuous Integration, Graph Database, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Tensorflow, Software Engineering, Reinforcement Learning, Pytorch, Large Language Models, Integration Tests, Artificial Intelligence Markup Language (AIML)
- **Published:** September 8, 2026
- **Apply:** https://www.careerjet.com/job/usc83fd1053fe6729379f7165711cd286b/eaa

## About the Role

* 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.

## Description

* 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.


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