JPMorgan Chase has 448 active AI-related job listings. The majority of these roles, 55%, are focused on agents, with application roles making up another 17%. The dominant function for these positions is Engineering, with a significant number of roles also in Product. The company is primarily hiring in the United States, followed by the United Kingdom and India. Frequent tech tags include agent_orchestration, llm_observability, and model_serving. In the last 30 days, JPMorgan Chase posted 275 new AI roles, representing a 76% increase compared to the previous 30-day period.
Currently tracking 305 active AI roles, with 1184 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $153k–$285k (avg $226k).
JPMorgan Chase currently has 445 active AI-related roles in our index. The most common open titles are: Data Scientist [Multiple Positions Available] (7), Lead Software Engineer (6), Applied AI ML-Vice President (4), Applied AI/ML Lead (4), Applied AI ML-Senior Associate (3). Most positions are in Engineering and Product.
JPMorgan Chase's active AI hiring is concentrated in: agents (57%), application (17%), serving infrastructure (9%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
JPMorgan Chase is hiring AI talent in: United States (299 roles), United Kingdom (64 roles), India (56 roles), Singapore (16 roles).
Job postings at JPMorgan Chase most frequently mention: Machine Learning, Agentic Systems, Statistics, Data Science, Large Language Models (LLMs).
In the past 30 days, JPMorgan Chase has posted 178 new AI-related roles. That is a -35% change versus the prior 30 days (274 → 178).
| Title | Stage | AI score |
|---|---|---|
| AI Researcher - Senior Associate AI Researcher Senior Associate at JPMorgan Chase, focused on developing novel AI/ML techniques and models for complex, large-scale problems within the financial services domain. The role involves research projects, formulating problems, developing algorithms, conducting experiments, and contributing to business applications, open-source software, and patents. | Post-train | 8 |
| NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence Research Scientist role focused on applying sophisticated machine learning methods, particularly NLP and LLMs, to real-world problems within a financial services context. The role involves developing state-of-the-art models, publishing research, and collaborating to deploy solutions into production. It emphasizes both research exploration and practical application, with a focus on post-training and potentially agentic systems. |
| 8 |
| Applied AI ML Senior Associate - Machine Learning Center of Excellence - Time Series Reinforcement Learning This role focuses on applying advanced ML methods like time series analysis, reinforcement learning, causal inference, and NLP to solve real-world problems in finance. The associate will research new methods, develop state-of-the-art models, collaborate with various teams to deploy solutions, and drive firm-wide initiatives. A PhD in a quantitative discipline and hands-on experience with ML toolkits are required, with a preference for candidates with financial industry knowledge and published research. | Post-trainAgent | 8 |
| Quantitative Trading & Research - Mid-Frequency Trading Strategies - Vice President / Executive Director Quantitative research role focused on developing and implementing mid-frequency trading strategies using advanced statistical modeling and machine learning techniques. The role involves the full lifecycle from ideation and research to production deployment and performance monitoring, with a strong emphasis on extracting predictive signals from complex financial datasets. | Agent | 7 |
| Experience Research Associate This role focuses on user research within a financial enterprise, with a secondary emphasis on exploring and evaluating AI tools for research operations. The primary function is to support and conduct user research, analyze data, and inform user experience design decisions. While AI tools are mentioned, the core of the role is traditional UX research, not AI model development or deployment. | — | 1 |
| Cross-Asset Risk Premia Research – Quantitative Strategist – Vice President Quantitative Strategist role focused on cross-asset risk premia research, contributing to publications, and collaborating with internal and external stakeholders. Requires a quantitative degree, strong analytical and coding skills (Python), and knowledge of machine learning and big data. | — | 0 |
| Experience Research Vice President - Cybersecurity Technology and Controls This role focuses on user experience research within Cybersecurity Technology and Controls at JPMorgan Chase, aiming to shape product design by uncovering customer needs and behaviors. It involves designing and executing research studies, analyzing data using advanced methods, and mentoring junior researchers. While it mentions AI tooling as a preferred skill, the core function is user experience research, not AI model development. | — | 0 |
| Quantitative Trading & Research - Market Microstructure & High Frequency Trading Specialist - Vice President Quantitative trading and research role focused on designing and implementing systematic trading strategies for FX, Rates, Commodities, and Credit markets, with an emphasis on market microstructure and high-frequency trading. Responsibilities include analyzing market data, generating signals, and collaborating with technology partners. | — | 0 |