2026 Machine Learning Center of Excellence (Time Series & Reinforcement Learning) - Summer Associate

Overview

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. The Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy machine learning solutions for our most challenging business problems. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

 

Position

As a Summer Associate within the MLCOE, you will apply sophisticated machine learning methods to a wide variety of complex domains including natural language processing, large language models, speech recognition and understanding, reinforcement learning, and recommendation systems. You must excel in a highly collaborative environment with MLCOE mentors, business experts, and technologists to conduct independent research and deploy solutions into production. You should have a strong passion for machine learning, solid expertise in deep learning with hands-on implementation experience, and a commitment to learning, researching, and experimenting with innovations in the field. Learn more about our MLCOE team at jp morgan.com/mlcoe.

 

Program Details

Our Summer Associate Internship Program begins in June, depending on your academic calendar. Your professional growth and development will be supported through project work related to your academic and professional interests, mentorship, an engaging speaker series with senior leaders, and more. Your project will have direct impact on JPMorgan’s businesses, will be integrated into our product pipelines, or be part of published research in top AI/ML conferences. Full-time employment offers may be extended upon successful completion of the program.

 

Job responsibilities

• Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation, and participation in our knowledge-sharing community.
• Develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks such as time-series predictions, market modeling, and decision optimizations.
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production.

 

Required qualifications, capabilities, and skills

• Ph.D. or in the last year of a Ph.D. program in machine learning, statistics, mathematics, computer science, economics, finance, science, engineering, or other quantitative fields
• Knowledge of machine learning / data science theory, techniques, and tools
• Scientific thinking, ability to work with literature, and the ability to implement complex projects
• Ability to understand business problems, study literature for solution approaches, write high-quality code for the chosen method, design training and experimentation to validate algorithms and implementations, and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
• Solid written and spoken communication to effectively convey technical concepts and results to both technical and business audiences
• Ability to work both independently and in highly collaborative team environments
• Excellent analytical, quantitative, and problem-solving skills with demonstrated research ability
• Curious, hardworking, detail-oriented, and motivated by complex analytical problems

 

Preferred qualifications, capabilities, and skills

• Knowledge of Financial Mathematics, Stochastic Calculus, Bayesian techniques, Statistics, State-Space models, MCMC, DSGE models, MCTS / distributed compute, NLP, accounting
• Knowledge and experience with Reinforcement Learning methods
• Knowledge of Python, TensorFlow, tf-agent, Ray, RLLib, Tune, or other ML frameworks
• Experience with OOP, graph-based computation engines, large-scale software development, C++/Java/CUDA, performance-focused implementations, numerical algorithms, distributed computing, cloud computing, and data transformation pipelines
• Familiarity with continuous integration models and unit test development
• Published research in NLP, speech recognition, reinforcement learning, or deep learning at a major conference or journal
• Strong passion for machine learning and a habit of investing independent time in learning, researching, and experimenting with innovations across fields

 

#MLCOE_jobs

J.P. Morgan is a global leader in financial services, providing strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. Our first-class business in a first-class way approach drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

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 protected attributes including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy, disability, or any other basis protected under applicable law. We also 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.

MLCOE is a world-class machine learning team with state-of-the-art methods to solve financial problems using unique datasets.