Machine Learning Engineer

Trading Interview; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Jane Street seeks an ML engineer to join our growing ML team in New York. You will work on our ML platform, APIs, and systems designed for rapid experimentation and production readiness.

We value deep mathematical intuition, curiosity about modern ML methods, and the ability to maintain clean, reproducible research code that scales as our platform evolves.

Qualifications

• Experience building training and inference infrastructure.
• Strong mathematical background including optimization theory and linear algebra.
• Curiosity for state-of-the-art ML methods and papers.
• Ability to maintain robust, reproducible research codebases.

Responsibilities

• Build and maintain training and inference infrastructure to production.
• Move ideas from concept to production with reliability.
• Advance research workflows to tighten feedback loops.

Skills

ML engineering

Mathematical foundations

Optimization theory

Regularization techniques

Research codebase organization

State-of-the-art awareness

Tools

PyTorch

Jax

TensorFlow

Job description

We are looking for an 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 engineers will be able to understand the mechanics behind various modeling techniques, while also being able to break down the mathematics behind them.

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 optimization theory, regularization 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 organized 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

This description was published by Jane Street.

We were founded by a small group of traders and technologists in a tiny New York office. Today, we have more than 2,000 employees across five global offices. We trade…