The Machine Learning Center of Excellence (MLCOE) at J.P. Morgan is looking to solve real-world financial problems using state-of-the-art machine learning methods and the company's vast and unique datasets.
Requirements
- Solid programming skills with C/C++, Python, JAVA or other equivalent languages
- Deep knowledge in Machine Learning, Data Mining, Applied Mathematics, Optimization, and Statistics
- Knowledge with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, JAX) and ETL pipelines, both batch and real-time data processing
- Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- CPU, 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, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
- Develop state-of-the art machine learning models to solve real-world problems and apply it to different tasks
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
Other
- Enrolled in a PhD or MS program in Computer Science, Physics, Mathematics, Engineering or related quantitative field with an expected graduation date of December 2026 through August 2027
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical, and business audiences
- Ability to work both independently and in highly collaborative team environments
- Interest in quantitative finance and/or portfolio management
