Machine Learning Researcher
About the role
We’re looking for smart and curious individuals to join our growing 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. 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. 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.
Responsibilities
- Build deep learning models that power trading strategies and train models for the next generation of deep learning-based trading approaches.
- Work with a rapidly growing computing cluster with tens of thousands of GPUs.
- Dive into market data, tune hyperparameters, and debug distributed training performance.
- Study how models trade in production and contribute to model selection and evaluation across markets and situations.
- Leverage knowledge across ML landscape (LLMs, vision, RL, recommendations, classical ML) to shape ML at Jane Street.
- Hire new colleagues, attend conferences, and teach techniques to teammates.
Qualifications
- Practical experience working on empirical ML problems
- Ability to apply logical and mathematical thinking to 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
- Hands-on coding skills in Python and preferred ML framework
- Willingness to ask questions, admit mistakes and learn new things
- Fluency in English
Skills
About Jane Street
SIX
Jane Street is a quantitative trading firm and liquidity provider with a unique focus on technology and collaborative problem solving.
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