Machine Learning Researcher

2 requirements, read out of the advert rather than guessed from the job title:

• Python
• machine learning

See how often each of these is required across open data roles in Europe.

About the Position

Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Researcher while also providing a truly unparalleled educational experience. You'll work side by side with experienced ML Researchers on projects that we've selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how we think about markets through challenging classes and activities, and practice using established methods alongside our own unique twists to train practical models.

At Jane Street, the lines between research, technology, and trading are intentionally blurry, and you’ll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. Trading poses unusual challenges—large models and nonstationary datasets in a competitive multi-agent environment—that force us to search for novel techniques.

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.