Artificial Intelligence Research - Senior Associate

JPMorganChase AI Research is a global team focused on developing novel AI capabilities for the financial services sector. As a Senior Associate, you will work on innovative techniques and frameworks to address complex problems, collaborating with various teams to ensure high-quality delivery of AI 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

Preferred

• Practical experience with ML libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.) and agent frameworks (e.g. LangGraph, Google ADK, etc.)
• Familiarity with common formal verification tools and languages (e.g., Coq/Isabelle/Lean, TLA+, Alloy, Z3, PDDL)
• Practical software development experience in collaborative project settings such as open-source projects or industry experience
• Proven ability to translate business requirements into technical problem formations and deliver novel solutions into production
• ML libraries experience
• PyTorch proficiency
• TensorFlow/Keras proficiency
• HuggingFace Transformers experience
• agent frameworks knowledge
• LangGraph knowledge
• Google ADK knowledge
• formal verification tools familiarity
• Coq knowledge
• Isabelle knowledge
• Lean knowledge
• TLA+ knowledge
• Alloy knowledge
• Z3 knowledge
• PDDL knowledge
• software development experience
• collaborative project experience
• open-source project experience
• industry experience
• business requirements translation
• technical problem formation
• novel solutions delivery

Benefits

• 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

• Fresh PhD or MS in Computer science, Engineering, or related fields with relevant research experience in AI/ML with 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
• Ability to deliver modular, optimized, high-quality Python code with tests
• 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
• Motivated to make an impact on problems in the financial services domain.Curiosity, creativity, resourcefulness, and a collaborative spirit
• We are looking for researchers across multiple areas of specialization, including: Synthetic Data Generation across multiple modalities (tabular, images, time-series, etc.), synthetic personas and agent simulations - Multimodal agent security and safety, alignment, guardrails, red teaming, data privacy and unlearning. Continual learning for agents (e.g. memory-based, model-based including reinforcement learning and post-training). Advanced multi-agent systems including co-ordination, negotiation, deep research, and hybrid / neuro-symbolic approaches. Foundation model training for tabular, time-series, language and other modalities. Multimodal information discovery, understanding and predictive modeling spanning multiple modalities e.g. websites, news, audio, speech, documents, images, etc. Formal methods (e.g., temporal logic, constraint programming, model checking, automated planning, theorem proving, SMT/SAT solving) and program/hardware verification
• Practical experience with ML libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.) and agent frameworks (e.g. LangGraph, Google ADK, etc.)
• Familiarity with common formal verification tools and languages (e.g., Coq/Isabelle/Lean, TLA+, Alloy, Z3, PDDL)
• Practical software development experience in collaborative project settings such as open-source projects or industry experience
• Proven ability to translate business requirements into technical problem formations and deliver novel solutions into production

Required skills

• Agent Security and Safety, Agent Simulations, Alloy, Artificial Intelligence, Automated Planning, Benchmarking and Metrics, Constraint Programming, Coq, Data Privacy, Experimental Design, Formal Methods, Foundation Model Training, Google ADK, HuggingFace Transformers, Isabelle, Keras, LangGraph, Lean, Machine Learning, Model Checking, Multi-agent Systems, Multimodal AI, Neuro-symbolic Approaches, PDDL, PyTorch, Python, Reinforcement Learning, SMT/SAT Solving, Statistical Data Analysis, Synthetic Data Generation, TLA+, Temporal Logic, TensorFlow, Theorem Proving, Unlearning, Z3

Experience

• 2+ years