Artificial Intelligence Research Director - Executive Director

JPMorganChase AI Research develops novel artificial intelligence capabilities and translates AI and machine learning techniques into secure, reliable, and scalable financial-services solutions. The Executive Director / Research Director will lead commercially oriented research projects, develop algorithms and models for complex large-scale problems, guide strategic research portfolios, and collaborate with data science, engineering, product, and business stakeholders to deliver production-ready solutions.

Responsibilities

• Work on multiple commercially oriented research projects in collaboration with internal data scientists, applied engineering teams and stakeholders across businesses e.g. Commercial & Investment Banking (including Markets), Asset & Wealth Management, Consumer & Community Banking, etc
• Formulate problems, generate hypotheses, develop new algorithms and models, conduct experiments and rigorous evaluations, synthesize and communicate results, and deliver well-tested, high-quality code
• Contribute to high-impact business applications, reusable assets and products, and research initiatives
• Provide thought leadership on internal and external forums through white papers, publications and presentations
• Own a portfolio of capabilities, drive strategic directions and prioritization within the portfolio including business stakeholder engagement, development of relevant reusable capabilities or products, and initiation of new research initiatives that can drive business impact

Preferred

• Practical experience with ML/RL libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.), familiarity with common formal verification tools and languages (e.g., Coq/Isabelle/Lean, TLA+, Alloy, Z3, PDDL)
• ML libraries experience
• PyTorch proficiency
• TensorFlow/Keras proficiency
• HuggingFace Transformers experience
• formal verification tools familiarity
• Coq knowledge
• Isabelle knowledge
• Lean knowledge
• TLA+ knowledge
• Alloy knowledge
• Z3 knowledge
• PDDL knowledge

Benefits

• 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.
• Comprehensive health care coverage
• On-site health and wellness centers
• A retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching

Company

• Global financial institution offering banking, asset management, and advisory services
• New York, New York, USA
• https://www.jpmorganchase.com/
• Founded in 2000
• 10001+ employees

Qualifications

• PhD in Computer Science, Engineering, or related fields with relevant research experience in AI/ML and 4+ years of relevant work experience
• Research publications in top-tier AI/ML venues (e.g., conferences, journals) – broad conferences such as NeurIPS, ICML, ICLR, etc., or highly regarded specialized conferences such as ICAPS, CRYPTO, etc
• Deep understanding of fundamental AI/ML techniques and a strong grasp of current state of the art in specific areas of expertise
• Effective verbal and written communication skills with the ability to address both technical and business audiences
• Practical software development experience in collaborative project settings such as open-source projects or industry experience. Ability to deliver modular, optimized, high-quality Python code with tests
• Experience leading and mentoring AI researchers, partnering with engineering and business stakeholders to drive execution and strategic planning across near-term deliveries and longer-horizon research initiatives
• Demonstrated ability to translate research into real-world impact e.g., production-ready solutions, prototypes/pilots, reusable components, reference architectures, or standards
• Ideal candidate enjoys being hands-on and deeply involved with the team in vetting design, solution approaches, results and code
• Deep research expertise in multi-agent systems and reinforcement learning including agent co-ordination, negotiation, communication, simulations and mechanism design
• Hands-on experience building and deploying multi-agent solutions with frameworks such as Google ADK, LangGraph, A2A, etc. Strong understanding of technical architectures, design and tradeoffs
• Practical experience with ML/RL libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.), familiarity with common formal verification tools and languages (e.g., Coq/Isabelle/Lean, TLA+, Alloy, Z3, PDDL)

Required skills

• A2A, AI/ML Research Publications, Artificial Intelligence and Machine Learning, Google ADK, Hugging Face Transformers, LangGraph, Leadership and mentoring, Mechanism Design, Multi-Agent Systems, PyTorch, Python, Reinforcement Learning, TensorFlow/Keras

Experience

• 4+ years