ꓟachine ꓡearning ꓣesearcher

You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored dataset, try a new modelling paradigm for a thorny problem, or consider blue-sky approaches that we're still trying to figure out. The problems we work on rarely have clean, definitive answers, and they often require insights from colleagues across the firm with different areas of expertise. Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging training issues, or analysing the predictions your model makes. Note that given the IP-sensitive nature of machine learning research at Jane Street, it is unlikely that any research findings associated with the internship will be suitable for outside academic publication. About you If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here.

If you have a curious mind and a passion for solving interesting problems, we have a feeling you'll fit right in. We're more interested in how you think and learn than what you currently know. You should be: 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 If you'd like to learn more, you can read about our interview process and meet some of the team. Learn more about Jane Street's internship program here.