Machine Learning Researcher

Jane Street Jane Street · Quant · New York, NY · Machine Learning

Machine Learning Researcher to build deep learning models for trading strategies, supported by a large GPU cluster. The role involves tackling challenges like large models, nonstationary datasets, and multi-agent environments, requiring novel techniques. Researchers collaborate closely with engineers and traders, diving into market data, hyperparameter tuning, distributed training, and model behavior in production. The position requires in-depth knowledge of ML, including LLMs, image models, RL agents, recommendation systems, and classical ML, to shape the future of ML at Jane Street. Responsibilities include training next-generation models, building fundamental understanding for new markets, hiring, attending conferences, and teaching teammates.

What you'd actually do

  1. build the deep learning models that power our trading strategies
  2. train models for the next generation of our deep learning-based trading strategies
  3. build the fundamental understanding we need to tackle new markets and situations
  4. hiring new colleagues, attending conferences, and teaching techniques to teammates

Skills

Required

  • 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

What the JD emphasized

  • large models
  • nonstationary datasets
  • multi-agent environment
  • novel techniques

Other signals

  • novel techniques
  • large models
  • nonstationary datasets
  • multi-agent environment
  • deep learning models
  • trading strategies