Job Responsibilities
- Create state‑of‑the‑art machine learning models to solve real‑world problems and apply them to NLP, speech recognition and analytics, time‑series predictions, or recommendation systems.
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
- Drive firm‑wide initiatives by developing large‑scale frameworks to accelerate the application of machine learning models across different areas of the business.
- Research and explore new machine learning methods through independent study, attending industry‑leading conferences, experimentation and participation in knowledge‑sharing community.
Required Qualifications, Capabilities, and Skills
- PhD in a quantitative discipline (Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science) or an MS with significant industry or research experience.
- Solid background in NLP, LLM, and graph analytics plus hands‑on experience and solid understanding of machine learning and deep learning methods.
- Hands‑on experience building agentic AI / multi‑agent systems within regulated or compliance‑driven environments.
- Ability to design experiments and training frameworks, outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals, focusing on agentic systems and LLM evaluation.
- Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Scientific thinking with ability to invent and work independently and in highly collaborative teams.
- Motivated by complex analytical problems; curious, hardworking, detail‑oriented.
Preferred Qualifications, Capabilities, and Skills
- Strong background in Mathematics and Statistics and familiarity with financial services industry and continuous integration models and unit test development.
- Knowledge of graph integration with LLM, reinforcement learning or meta‑learning.
- Experience with A/B experimentation and data/metric‑driven product development, cloud‑native deployment in a large‑scale distributed environment, and ability to develop and debug production‑quality code.
- Published research in machine learning, deep learning or reinforcement learning at a major conference or journal.
About the Job
The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. The Applied AI ML Director – NLP / LLM and Graphs role will apply sophisticated machine learning methods to complex tasks including natural language processing, graph analytics, speech analytics, time series, reinforcement learning and recommendation systems, and collaborate with various teams.
We value solid expertise in deep learning with hands‑on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.
EEO Statement
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal‑opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of any protected attribute and make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
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