Machine Learning Researcher

1 Month ago • All levels • Research Development

Job Summary

Job Description

We are seeking smart and curious individuals to join our Machine Learning team, focusing on building deep learning models for trading strategies. This role involves working with a large computing cluster, tackling challenges like large models and nonstationary datasets in a competitive multi-agent environment. You will apply your knowledge of various ML approaches (LLMs, image models, RL agents, etc.) to develop next-generation trading strategies and understand new markets. The role also includes hiring, conference attendance, and teaching. We are looking for individuals with practical ML experience, strong logical and mathematical thinking, intellectual curiosity, coding skills in Python, and a passion for learning.
Must have:
  • Practical experience in empirical ML
  • Strong logical and mathematical thinking
  • Intellectual curiosity in state-of-the-art ML research
  • Fluency with versatile ML models and techniques
  • Hands-on coding skills for rapid iteration
  • Proficiency in Python and an ML framework
  • Eagerness to learn and ask questions
  • Fluency in English

Job Details

About the position

We’re looking for smart and curious individuals from industry and 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 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.

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 favourite ML framework
  • An eagerness to ask questions, admit mistakes and learn new things
  • Fluency in English

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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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