Jane StreetOfficial careers listing

Posted 1mo ago

Machine Learning Research Engineer

Pay

Not stated

Location

Hong Kong, Hong Kong

On site

Skills this role screens for

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Responsibilities

What you'll do

  • Help drive the direction of the ML platform
  • Aid decision-making to apply the right ML tool for the problem
  • Enhance research workflows to tighten feedback cycles
  • Understand mechanics and mathematics behind various modeling techniques
  • Bridge between research and engineering
  • Push forward the frontier of model capabilities at all points of the stack
  • Enable new scale in the technology stack
  • Rapidly prototype new research ideas with Researchers
  • Build workflow APIs that support a wide range of use cases

Requirements

What they're looking for

  • Robust experience in machine learning
  • Strong mathematical foundations
  • In-depth knowledge of the ML ecosystem
  • Understanding of varying ML approaches (neural networks, random forests, gradient-boosted trees, ensemble methods)
  • Experience building and maintaining training and inference infrastructure
  • Understanding of moving ML from concept to production
  • Strong mathematical background (optimization theory, regularization techniques, linear algebra)
  • Passion for keeping up with state-of-the-art ML (academic papers, new hardware, ML package source)
  • Proven ability to create and maintain an organized, robust, reproducible research codebase
  • Expertise wrangling an ML framework (PyTorch, Jax, TensorFlow or others)
  • Inventive approach to ML problems
  • Willingness to ask hard questions about approaches and tools
Full description from the employer

We are looking for a Research Engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Our ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use. We’ll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches - whether it’s neural networks, random forests, gradient-boosted trees or sophisticated ensemble methods - to aid decision-making so we apply the right tool for the problem at hand. Your work will also focus on enhancing research workflows to tighten our feedback cycles. Successful ML Research Engineers will be able to understand the mechanics behind various modelling techniques, while also being able to break down the mathematics behind them. We’re looking for people who can be a true bridge between research and engineering, and can help us push forward the frontier of our model capabilities at all points of the stack. This could involve enabling a new scale in our technology stack, sitting on a team of Researchers to rapidly prototype a new research idea, or building workflow APIs that support a wide range of use cases. 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. While there isn’t a fixed list of qualifications we’re looking for, if you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in. We're looking for someone with: • Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production • A strong mathematical background; Good candidates will be excited about things like optimisation theory, regularisation techniques, linear algebra and the like • A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware or reading the source of a new machine learning package • A proven ability to create and maintain an organised research codebase that produces robust, reproducible results while maintaining ease of use • Expertise wrangling an ML framework – we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow or others • An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools • Fluent in English If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

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