Machine Learning Researcher

1 Month ago • All levels • Research Development

Job Summary

Job Description

The Machine Learning team at Jane Street is seeking smart and curious individuals from academia to build deep learning models that power their trading strategies. Researchers, engineers, and traders collaborate to train models, architect systems, and run trading strategies, addressing challenges like extreme latency constraints and complex feedback loops. The role involves diving into market data, tuning hyperparameters, debugging distributed training performance, and studying model behavior in production. Candidates will leverage their ML knowledge to shape the future of ML, train models, and build understanding for new markets. This includes hiring colleagues, attending conferences, and teaching techniques.
Must have:
  • Practical experience working on empirical ML problems.
  • Ability to apply logical and mathematical thinking to solve problems.
  • Intellectual curiosity and excitement about state-of-the-art research.
  • Fluency with a versatile set of models and tricks.
  • Hands-on coding skills in Python and a favorite ML framework.

Job Details

About the Position

We’re looking for smart and curious individuals from academia 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 thousands of H100s/200s. Trading poses unusual challenges—extreme latency constraints, large datasets, complex feedback loops, and a high level of noise—that force us to search for novel tricks. 

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. You’ll also be hiring new colleagues, attending conferences, and teaching techniques to teammates—all of which we consider to be real and impactful parts of the job.

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. There’s no fixed set of skills we are looking for, but you should bring:

  • 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're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

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About The Company

Jane Street is a quantitative trading firm with offices in New York, London, Hong Kong, Singapore, and Amsterdam. We are always recruiting top candidates and we invest heavily in teaching and training. The environment at Jane Street is open, informal, intellectual, and fun. People grow into long careers here because there are always new and interesting problems to solve, systems to build, and theories to test.



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