Location
London

Hours
Full Time - Summer Internship Period (specific dates to be confirmed)

Salary
Competitive, commensurate with experience

About the Role
The Machine Learning Center of Excellence (MLCOE) at JPMorganChase is a world-class team dedicated to advancing state-of-the-art machine learning methods to solve complex, real-world financial problems using the company's vast and unique datasets. As a 2026 Summer Associate within MLCOE, you will apply advanced machine learning techniques across diverse domains including finance, banking, economics, marketing, natural language processing, reinforcement learning, accounting, and operations management.

You will create strategically important AI/ML applications within the Chief Data & Analytics office, impacting all lines of business such as Commercial & Investment Bank, Asset & Wealth Management, Consumer & Community Banking, and spanning front office sales and trading to operations, technology, and finance.

This role offers the opportunity to explore novel and complex challenges that could transform how the firm operates. You will collaborate closely with MLCOE mentors, business professionals, and technologists, conducting independent research and delivering innovative solutions aligned with business needs.

We seek candidates with a deep passion for machine learning, robust expertise in deep learning with practical implementation experience, and a strong dedication to learning, researching, and experimenting with innovations in the field.

Experience
- Enrolled in or completed a PhD in a quantitative discipline such as Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, Data Science, or related fields, or equivalent research/industry experience.
- Post-doctoral candidates and career changers are also welcome.
- Expected PhD graduation between December 2026 and August 2027, or already graduated.
- Strong background in programming, mathematics, and statistics, including Stochastic Calculus, Bayesian techniques, State-Space Models, MCMC, and MCTS.
- Published research in machine learning, science, engineering, quantitative psychology, business, or related fields.
- Knowledge and experience in Machine Learning and Reinforcement Learning, with familiarity in domains such as Finance, Economics, Accounting, Marketing, or Operations Research.
- Proficiency in Python and experience with machine learning/deep learning frameworks such as TensorFlow, TensorFlow Probability, and JAX.
- Ability to develop, debug, and maintain production-quality code, including familiarity with continuous integration and unit testing practices.

About You
- Scientific mindset with the ability to design experiments and training frameworks, and define and evaluate model performance metrics aligned to business objectives.
- Strong written and verbal communication skills, capable of explaining technical concepts and results to both technical and business audiences.
- Innovative, curious, hardworking, detail-oriented, and motivated by solving complex analytical problems.
- Able to work independently and collaboratively in team environments.
- Familiarity with the financial services industry and relevant certifications such as CFA, ACCA, PCAP, or other finance, accounting, programming, software engineering, Coursera, or equivalent professional qualifications is a plus.

Qualifications
- PhD or equivalent advanced degree in a relevant quantitative field.
- Demonstrated expertise in machine learning and reinforcement learning.
- Practical experience with deep learning frameworks and programming.
- Strong analytical, research, and problem-solving skills.
- Commitment to diversity, equity, and inclusion in the workplace.