Machine Learning Researcher
Jane StreetAbout the Role
A summer internship focused on machine learning research in systematic trading. You'll work alongside experienced ML Researchers on projects combining novel ML ideas with real-world trading relevance. You'll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and thousands of high-end GPUs to tackle unusual challenges in large model training and nonstationary datasets.
The bulk of your time will be spent collaborating with full-time researchers on their projects, which may include conducting end-to-end dataset studies, exploring new modeling paradigms for complex problems, or pursuing blue-sky research approaches. You'll engage in diverse activities—analyzing market data, tuning hyperparameters, debugging training issues, and interpreting model predictions—often requiring insights from colleagues across the firm.
Requirements
- An undergraduate, PhD student, or postdoc with practical experience working on ML problems
- Interested in applying logical and mathematical thinking to all kinds of problems
- Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn from many problem domains
- Fluent with a versatile set of models and tricks
- Able to rapidly implement and iterate on your ideas in Python and your favorite ML framework
- Eager to ask questions, admit mistakes, and learn new things