Machine Learning Researcher

Jane Street

$120K — $180K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience with empirical machine learning problems
  • Strong logical and mathematical problem-solving skills
  • Intellectual curiosity about state-of-the-art ML research
  • Proficiency with a variety of machine learning models and techniques
  • Hands-on coding skills in Python and familiarity with ML frameworks
  • Willingness to learn from mistakes and continuously improve

Responsibilities

  • Develop and optimize deep learning models for trading strategies
  • Leverage advanced computing resources with a focus on ML applications
  • Collaborate closely with researchers, engineers, and traders
  • Analyze market data and fine-tune hyperparameters
  • Debug and improve distributed training performance
  • Train new colleagues and share ML techniques
  • Participate in industry conferences to stay updated on the latest trends

Benefits

  • Collaborative team environment with direct communication
  • Access to extensive high-performance computing resources
  • Opportunity to influence the future of machine learning in finance
  • Professional development through conference attendance and knowledge sharing
  • Dynamic work atmosphere that encourages curiosity and innovation
Full Job Description
About the position

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. 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
  • An 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


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