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About the Role
We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and help drive the direction of our ML platform. Machine learning is a critical pillar of Jane Street's global business, and our trading environment serves as a unique, rapid-feedback platform for ML experimentation.
Responsibilities
- Aid decision-making by applying the right ML tool for the problem at hand.
- Enhance research workflows to tighten feedback cycles.
- Create and maintain an organized research codebase that produces robust, reproducible results while maintaining ease of use.
- Ask hard questions about whether we're taking the right approaches and using the right tools.
Requirements
- Robust experience in machine learning.
- Strong mathematical foundations.
- In-depth knowledge of the ML ecosystem and understanding of varying approaches (e.g., neural networks, random forests, gradient-boosted trees, ensemble methods).
- Understanding of the mechanics behind various modeling techniques and the mathematics behind them.
- Experience building and maintaining training and inference infrastructure.
- Understanding of what it takes to move from concept to production.
- Strong mathematical background, excited about optimization theory, regularization techniques, linear algebra, etc.
- Passion for keeping up with the state of the art (academic papers, latest hardware, new ML packages).
- Proven ability to create and maintain an organized research codebase.
- Expertise wrangling an ML framework (e.g., PyTorch, Jax, TensorFlow).
- Inventive approach.
- Willingness to ask hard questions about approaches and tools.
Skills
- Machine Learning
- Software Engineering
- API Design
- Systems Design
- Neural Networks
- Random Forests
- Gradient-Boosted Trees
- Ensemble Methods
- Optimization Theory
- Regularization Techniques
- Linear Algebra
- PyTorch
- Jax
- TensorFlow
About the Company
- Jane Street's global business relies on machine learning.
- Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation.
- Our ML team has a shared love for the craft of software engineering and for designing APIs and systems that are delightful to use.
- We are looking for individuals with a curious mind and a passion for solving interesting problems.