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 1181 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 reference: agent orchestration, llm observability, model serving, rag, fine tuning.
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 |
|---|---|---|
| Data Scientist [Multiple Positions Available] Data Scientist at JPMorgan Chase focused on building and training production-grade ML models for financial use cases, including forecasting, anomaly detection, NLP, and LLMs. Requires experience with deep learning, transformer models, and ML deployment in a financial domain. | Post-trainData | 8 |
| Applied AI ML Lead [Multiple Positions Available] Lead the development and deployment of AI/ML solutions for virtual assistants and transaction search applications within a financial services context. Focus on fine-tuning LLMs and SLMs, optimizing inference, and managing the release cycle for production-grade AI. | Post-trainServe |
| 8 |
| CCB Risk Modeling - AI ML Sr. Associate This role focuses on developing and deploying machine learning models for credit decisioning and fraud detection within a financial services context. Key areas include explainability, fairness, and responsible AI practices, with an emphasis on applying advanced ML techniques, including LLMs and agentic workflows, to complex business challenges. The role requires a strong background in model development, interpretability, and collaboration across various teams to ensure ethical and regulatory compliance. | Post-trainAgent | 8 |
| Asset Management - AI Quant Analyst - Artificial Intelligence & Machine Learning Focus JPMorgan Chase is seeking an AI Quant Analyst with a focus on AI/ML for their Asset Management division in Shanghai. The role involves researching and implementing quantitative investment models using ML/DL, applying LLMs/NLP to financial data for insights, and collaborating with teams to deploy models. The position requires a Master's or PhD in a quantitative field, 3+ years of experience in quantitative research within finance, and proven expertise in ML/DL/AI, particularly LLMs/NLP for financial data. Strong coding skills in Python and experience with statistical modeling are essential. The role also requires knowledge of financial markets and regulatory compliance. | Post-trainAgent | 8 |
| Lead Data Scientist - Finance Technology Lead Data Scientist for JPMorgan Chase's Finance Technology team, focusing on building and deploying production-grade AI/ML solutions, including LLMs, Gen AI, and agentic workflows, for finance processes. The role involves managing a global team and collaborating with business and technology partners. | Post-trainAgent | 8 |
| AI Research Lead (Natural Language Processing) - Vice President AI Research Lead focusing on Natural Language Processing within the financial services domain, developing novel techniques and state-of-the-art ML models for commercial applications. | Post-train | 8 |
| AI Research Scientist - Senior Associate AI Research Scientist role at JPMorgan Chase focused on developing novel techniques, tools, and frameworks for large-scale problems in financial services. The role involves formulating problems, developing algorithms and models, conducting experiments, and contributing to business applications, open-source software, and patents. | Post-train | 8 |
| AI Research Scientist - Senior Associate AI Research Scientist role at JPMorgan Chase focused on developing novel techniques, tools, and frameworks for large-scale problems in financial services. The role involves formulating problems, developing algorithms and models, conducting experiments, and contributing to business applications, open-source software, and patents. | Post-train | 8 |
| Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of Excellence Machine Learning Scientist - NLP - VP role focused on developing and deploying Generative AI solutions within JPMorgan Chase's Machine Learning Center of Excellence. The role involves research, thought partnership, cross-functional collaboration, and leading firm-wide initiatives to apply ML models across the business. Requires a PhD or MS with experience in GenAI, ML/DL toolkits, experimental design, and communication skills. | Post-trainAgent | 8 |
| Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate - Machine Learning Center of Excellence Machine Learning Scientist specializing in NLP and Generative AI (GenAI) to develop and deploy state-of-the-art models for complex business challenges within JPMorgan Chase. The role involves research, thought partnership with leaders, cross-functional collaboration for production deployment, and leading firm-wide initiatives with large-scale frameworks. Requires a PhD or MS with experience in GenAI, ML/DL toolkits, experiment design, and communication skills. | Post-trainAgent | 8 |
| Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of Excellence Machine Learning Scientist (VP) in the Machine Learning Center of Excellence at JPMorgan Chase, focusing on NLP and Generative AI. The role involves owning the full lifecycle of ML solutions, from research and development to production deployment, acting as a thought leader, and driving cross-functional collaboration to implement new ML methods and large-scale frameworks for business impact within the financial services industry. | Post-trainAgent | 8 |
| Applied AI ML Director JPMorgan Chase is seeking an Applied AI ML Director in London to lead a team of specialists in developing horizontal AI capabilities (APIs, libraries) for Corporate and Investment Banking. The role involves collaborating with Line of Business AI teams, mentoring engineers, and staying at the forefront of AI advancements, with a focus on domains like Documents, Email, and Speech. Requires a PhD or top commercial AI lab experience, hands-on model training/deployment, and experience leading AI teams. | Post-trainServe | 8 |
| 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 |
| AWM Risk Analytics Group – Data Scientist - Vice President Vice President Data Scientist role in JPMorgan's Asset & Wealth Management Risk Analytics Group, focusing on developing and deploying advanced AI/ML and LLM solutions for risk management. Responsibilities include identifying use cases, leading model development (pre-training, fine-tuning, optimization), prompt engineering, quantization, evaluation, and collaborating on model serving systems. Requires strong Python, SQL, R, PyTorch/TensorFlow, AWS, and NLP/LLM experience, with frameworks like LangChain/LangGraph/AutoGen. | Post-trainServe | 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. | Post-trainAgent | 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 |
| Principal Technical Program Manager- AI/ML- Payments This role is for a Principal Technical Program Manager to lead the end-to-end delivery of a Large Payments Model (LPM), a domain-specific foundation model trained on structured payments data for prediction and classification tasks within JPMorgan Chase's Payments Technology Team. The role involves coordinating Applied AI/ML, engineering, data pipelines, and governance/controls to ensure successful training, serving, integration, and adoption of the model. | Post-trainServe | 7 |
| Applied AI ML [Multiple Positions Available] This role involves applying statistical and machine learning methodologies, including causal inference, to solve business problems within a fintech domain. The individual will perform quantitative analysis, build and deploy prototype solutions, and mentor junior team members. A PhD or Master's degree with relevant experience is required, along with expertise in various analytical methods and programming languages like R. | Post-train | 7 |
| Business Banking - Data Scientist [Multiple Positions Available] Data Scientist role at JPMorgan Chase focused on developing and deploying machine learning models for financial prediction, trend identification, risk analysis, and anomaly detection within business banking portfolios. The role involves data processing, wrangling, ETL, automation, and leveraging visualization tools. Requires experience with Python, scikit-learn, SQL, and various BI software. | Post-trainData | 7 |
| Applied AI ML Lead Lead role in a Fintech company focused on designing and delivering innovative AI/ML models for financial analysis, regulatory requirements, and pricing decisions. Requires strong quantitative, programming (Python, PySpark), and machine learning skills, with experience in leading teams and communicating complex concepts. | Post-train | 7 |
| AI-ML Modeler Senior Associate Senior Associate AI-ML Modeler in the Finance Modeling team at JPMorgan Chase. The role involves designing and delivering innovative models for budgeting, financial analysis, regulatory requirements, and pricing decisions. Responsibilities include data anomaly identification, quantitative analysis, data cleaning, model building (statistical, econometric, ML), communicating results to stakeholders, and mentoring team members. Requires a graduate degree, 5+ years of model development experience, proficiency in Python/R/Scala, experience with specific financial models (budget, CCAR, PPNR), statistical/econometric techniques, machine learning theory, big data tools (Spark/Hadoop), and explainability for risk and compliance. Familiarity with Gen AI is preferred. | Post-train | 7 |
| Quantitative Trading and Research - Securitized Products Group - Associate Quantitative modeling role focused on Residential Mortgage-Backed Securities (RMBS) and structured products. The role involves applying machine learning and generative AI to enhance financial models for trading, valuation, and risk management, including data processing, calibration, and performance monitoring. | Post-train | 7 |
| Quantitative Trading & Research - Mid-Frequency Trading Strategies - Vice President Quantitative trading firm seeks a VP to research, develop, and deploy mid-frequency systematic trading strategies. Role involves applying statistical modeling and machine learning to financial markets, with a focus on alpha generation, portfolio construction, risk management, and execution. Requires end-to-end ownership from ideation to live trading and performance monitoring. | Post-trainServe | 7 |
| Conversation Designer Vice President This role is for a Conversation Designer Vice President within the Chase Digital Assistant team, focusing on shaping user experience for conversational AI products like chatbots and IVRs. The role involves leading the design of conversational flows, mentoring junior designers, collaborating with ML teams to refine NLU models, and driving the strategic vision for conversational AI in finance. | Post-trainAgent | 7 |
| WFP Lead Data Scientist - Vice President Lead Data Scientist for Workforce Planning at JPMorgan Chase, focusing on developing and deploying AI/ML models for forecasting, capacity planning, and scheduling. The role involves full model lifecycle management, project leadership, stakeholder collaboration, and mentoring junior team members, with an emphasis on moving towards real-time inference and decision-making. | Post-train | 7 |
| Sr Lead Software Engineer-Role DS Senior Lead Software Engineer at JPMorgan Chase focused on building and enhancing technology products. The role involves providing technical guidance, developing secure production code, influencing product design, and acting as a subject matter expert. Requires experience in machine learning, NLP, training/fine-tuning LLMs, transformer architectures, and deploying AI systems, with proficiency in Python, TensorFlow, or PyTorch. Experience with scalable distributed systems, cloud-native environments, and security protocols is also necessary. | Post-trainServe | 7 |
| Compliance - Applied AI/ML Lead - Vice President Lead Applied AI/ML role focused on developing and deploying models and analytical methods for compliance and risk management within a financial institution. Requires strong experience in Python, R, Scala, machine learning, statistical models, and specifically graph analytics and databases. The role involves data pipeline development, working with structured and unstructured data, and preparing technical documentation for governance review. | Post-trainData | 7 |
| Compliance - Quant Modeling Senior Associate (Fair Lending) - Associate This role focuses on applying quantitative modeling and statistical analysis to ensure fairness and compliance in line-of-business models, including traditional, ML/AI, and Gen AI models, within a regulated financial environment. The primary goal is to detect and mitigate bias to comply with Fair Lending Laws and regulations. | Post-train | 7 |
| Modeling Centre of Excellence: Forecasting_ Analyst Develops and industrializes quantitative methodologies and predictive models using statistical and machine learning techniques in R/Python for financial planning and forecasting within a large financial institution. The role involves data analysis, model development, documentation, and interaction with model governance. | Post-train | 7 |
| Modeling Centre of Excellence: Forecasting_ Associate Develops quantitative methodologies and predictive/explanatory models using statistical and machine learning techniques in R/Python for financial planning and forecasting within a large financial institution. The role involves data analysis, model development, documentation, and interaction with model governance. | Post-train | 7 |