2027 Machine Learning Center of Excellence - Time Series and Reinforcement Learning (TSRL) - Summer Associate

JPMorgan Chase & Co.•New York, NY

1d•$135,000 - $155,000

About The Position

The 2027 Machine Learning Center of Excellence (MLCOE) Time Series and Reinforcement Learning (TSRL) Summer Associate will join the Chief Data & Analytics Office at JPMorgan Chase. The MLCOE partners across the firm to create and deploy machine learning solutions for challenging business problems, while supporting data quality, integrity, and security and responsibly applying AI and machine learning to business goals, productivity, products, and risk management. The associate will work with technologists, machine learning researchers, and engineers to explore and apply current machine learning research to the firm’s data. The team collaborates with traders, portfolio managers, quants, data scientists, and salespeople to advance data-led transformation across the business. The internship program begins in June, depending on the academic calendar. It includes project work aligned with academic and professional interests, mentorship, and speaker sessions with senior leaders. Full-time employment offers may be extended after successful completion of the program.

Requirements

Be enrolled in a PhD or MS program in Econometrics, Finance/Accounting, Mathematics, Computer Science, Operations Research, or a related quantitative field, with an expected graduation date between December 2027 and August 2028.
Have solid programming skills in C/C++, Python, Java, or equivalent languages.
Have deep knowledge of machine learning, data mining, applied mathematics, optimization, and statistics.
Have knowledge of machine learning and deep learning toolkits such as TensorFlow, PyTorch, or JAX, and ETL pipelines for batch and real-time data processing.
Demonstrate scientific thinking and the ability to design experiments and training frameworks, and to define and evaluate intrinsic and extrinsic model-performance metrics aligned with business goals.
Have solid written and spoken communication skills to explain technical concepts and results to technical and business audiences.
Be able to work independently and in highly collaborative team environments.

Nice To Haves

Interest in quantitative finance and/or portfolio management.
Knowledge of CPU and GPU architecture, high-performance computing, and XLA compilers.
Experience in distributed system design and development.

Responsibilities

Research and explore new machine learning methods through independent study, attendance at industry-leading conferences, experimentation, and participation in the knowledge-sharing community.
Develop state-of-the-art machine learning models to solve real-world problems and apply them to different tasks.
Collaborate with Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management partner teams to deploy solutions into production.

Benefits

Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
Comprehensive health care coverage.
On-site health and wellness centers.
Retirement savings plan.
Backup childcare.
Tuition reimbursement.
Mental health support.
Financial coaching.
Internship mentorship, project work related to academic and professional interests, and speaker sessions with senior leaders.