ꓟachine ꓡearning ꓣesearcher
Jane StreetAbout the Role
Work side by side with experienced ML Researchers on projects combining novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how Jane Street thinks about markets through challenging classes and activities, practicing established methods and unique techniques to train practical models.
You'll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and tens of thousands of high-end GPUs. Spend the bulk of your internship on projects drawn from full-time researchers' work—conducting end-to-end studies of datasets, exploring new modelling paradigms, or developing blue-sky approaches. Tasks may include analyzing market data, tuning hyperparameters, debugging training issues, or evaluating model predictions.
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 favourite ML framework
- Eager to ask questions, admit mistakes, and learn new things
- Fluent in English