Jane Street is hiring a Machine Learning Researcher in Machine Learning — London, England, United Kingdom. The overview below is synthesized from the employer posting on janestreet.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
About the Position
Company context from the listing:
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.
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.
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
Company context from the listing:
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.
- 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.
Build a standout application
For the Machine Learning Researcher at Jane Street, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
Web3 hiring values reliability: on-time follow-through, clear writing, and a track record of improving runbooks and tooling. Treat the application as a work sample. For interviews, be ready to walk through how you prioritize across time zones, handle a difficult user, and decide when to escalate versus resolve directly. Show how you document decisions so the next teammate benefits.
In a distributed Web3 org, trust builds through written clarity. Use the cover note to demonstrate it.