Machine Learning Engineer
Jane Street2 months ago
Responsibilities
- Help drive the direction of Jane Street’s machine learning platform.
- Apply appropriate modeling techniques, including neural networks, random forests, gradient-boosted trees, and ensemble methods, to support decision-making.
- Build and maintain training and inference infrastructure and move ML systems from concept to production.
- Enhance research workflows to shorten feedback cycles.
- Design usable APIs and systems and maintain robust, reproducible research codebases.
Requirements
- Experience building and maintaining machine learning training and inference infrastructure and taking systems from concept to production.
- Strong mathematical background, including interest or knowledge in optimization theory, regularization techniques, and linear algebra.
- Ability to keep up with machine learning research, academic papers, hardware, and new machine learning packages.
- Proven ability to create and maintain organized research codebases that produce robust, reproducible results and remain easy to use.
- Expertise with an ML framework such as PyTorch, Jax, TensorFlow, or another framework.
- Inventive approach, curiosity, and willingness to question existing approaches and tools.
Tech Stack
PyTorchTensorFlow
Categories
About Jane Street
Jane Street is a global quantitative trading firm and liquidity provider that builds in-house software and research platforms to trade across asset classes. It makes markets and executes proprietary strategies on exchanges and electronic venues, serving institutional markets rather than individual investors. Founded in 2000 and headquartered in New York, it is privately held with offices in London, Hong Kong, Singapore, and Amsterdam.