2027 Machine Learning Center of Excellence (Quant AI) - Summer Associate

JPMorgan Chase & Co. • Palo Alto, CA

2d • $135,000 - $155,000

About The Position

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase accelerates the firm’s data and analytics journey. Within CDAO, the Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy machine learning solutions for challenging business problems. The office supports the quality, integrity, and security of company data and uses data to generate insights and inform decisions. It also develops and implements solutions that support commercial goals through responsible use of AI and machine learning to develop products, improve productivity, and enhance risk management.

As a Quant AI Summer Associate in the MLCOE, you will join technologists, machine learning researchers, and engineers focused on machine learning and scale. The team explores current research and applies machine learning techniques to JPMorgan Chase data, working with traders, portfolio managers, quants, data scientists, and salespeople to support data-led business transformation.

The Summer Associate Internship Program begins in June, depending on the participant’s academic calendar. The program supports professional development through project work related to academic and professional interests, mentorship, and speaker series with senior leaders. Full-time employment offers may be extended after successful completion of the program. Employment is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries, under Section 19 of the Federal Deposit Insurance Act.

Requirements

• Be enrolled in a PhD or MS program in Computer Science, Physics, Mathematics, Engineering, 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.
• Know 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 define and evaluate intrinsic and extrinsic model-performance metrics aligned with business goals.
• Have strong 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, industry conferences, experimentation, and participation in a 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 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.

What This Job Offers

• Career Level: Intern