Jane Street is hiring a Machine Learning Researcher in Machine Learning — New York, New York, United States. 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:
We’re looking for smart and curious individuals to join our growing team and drive our ML work.
On our Machine Learning team, you'll build the deep learning models that power our trading strategies, supported by our rapidly growing computing cluster with 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.
At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and work together to train models, architect systems, and run trading strategies. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance, or studying how our model likes to trade in production.
We’ll rely on your in-depth knowledge of the machine learning landscape and understanding of a variety of approaches—drawn from LLMs, image models, RL agents, recommendation systems, or classical ML methods—to shape the future of ML at Jane Street. You’ll train models for the next generation of our deep learning-based trading strategies, and build the fundamental understanding we need to tackle new markets and situations.
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.
- Practical experience working on empirical ML problems
- The ability to apply logical and mathematical thinking to all kinds of problems
- Intellectual curiosity and excitement about state-of-the-art research across many ML problem domains
- Fluency with a versatile set of models and tricks
- The hands-on coding skills needed to rapidly implement and iterate on your ideas, in Python and your favorite ML framework
- An eagerness to ask questions, admit mistakes, and learn new things
If you’d like to learn more, you can read about our interview process and meet some of the team.
If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.
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.
