Artificial Intelligence Research Lead - Vice President

JPMorganChase AI Research develops novel artificial intelligence capabilities and translates advanced AI and machine learning techniques into secure, reliable, scalable solutions for financial services. The Vice President / Research Lead will lead commercially oriented research projects, develop algorithms and models for complex problems, evaluate and communicate results, deliver high-quality code, and guide research initiatives from innovation through production-scale implementation.

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
• Lead projects or major workstreams in larger projects/initiatives. Play a key role in ensuring that problem definitions and solutions are technically sound, generalizable and capture business/product requirements
• Proactively identify and propose new research initiatives motivated by long-term business needs

Preferred

• (Depending on specialization) Practical experience with ML libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.), agent frameworks (e.g. LangGraph, Google ADK, etc.), 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
• agent frameworks knowledge
• LangGraph experience
• Google ADK knowledge
• formal verification tools
• Coq proficiency
• Isabelle proficiency
• Lean proficiency
• TLA+ knowledge
• Alloy knowledge
• Z3 knowledge
• PDDL knowledge

Benefits

• Commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, for those in eligible roles
• 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 2+ 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. Practical experience with statistical data analysis, experimental design and creation of meaningful benchmarks and metrics for evaluation
• 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
• Strong track record of research in one of the following areas: (a) Synthetic Data Generation across multiple modalities (tabular, images, time-series, etc.), synthetic personas and agent simulations, (b) Multimodal information discovery, understanding, research and analysis spanning multiple modalities e.g. websites, news, documents, structured data, images, etc., (c) Multimodal processing and predictive modeling, including input modalities like speech, audio, structured data, text, images
• (Depending on specialization) Practical experience with ML libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.), agent frameworks (e.g. LangGraph, Google ADK, etc.), common formal verification tools and languages (e.g., Coq/Isabelle/Lean, TLA+, Alloy, Z3, PDDL)

Required skills

• Artificial Intelligence and Machine Learning, Experimental Design, Formal Verification, Hugging Face Transformers, Leadership and Mentoring, Multimodal Processing and Predictive Modeling, PyTorch, Python, Research Publications, Software Development, Stakeholder Management, Statistical Data Analysis, Synthetic Data Generation, TensorFlow/Keras

Preferred skills

• Verbal and Written Communication

Experience

• 2+ years