---
title: 'Machine Learning Research Engineer at Jane Street'
canonical: 'https://feeny.ai/job/machine-learning-research-engineer-jane-street-new-york-j4dnerb1bzqa'
type: 'job'
last_seen: '2026-10-15'
---

# Machine Learning Research Engineer at Jane Street

- **Company:** Jane Street
- **Location:** New York, NY
- **Posted:** 2022-11-18
- **Last confirmed live:** 2026-10-15
- **Apply:** https://www.janestreet.com/join-jane-street/apply/6485460002?gh_jid=6485460002

## Job description

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](https://www.janestreet.com/join-jane-street/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 modeling 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 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

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

## About Jane Street

## Company Overview
- **One-liner**: Jane Street is a global quantitative trading firm and liquidity provider that uses sophisticated technology, machine learning, and deep market expertise to trade financial products across equities, bonds, options, and ETFs.
- **Entity Type**: Private (not publicly traded)
- **Headquarters**: New York, USA (with offices in London, Hong Kong, Singapore, and Amsterdam)
- **Founded**: 2000
- **Founders**: Not publicly disclosed as a single founder group; the firm was founded by a team of quantitative traders and technologists.

## Core Business
- **Primary industry/industries**: Quantitative finance / Proprietary trading / Market making
- **Target customers**: Institutional clients (asset managers, pension funds, insurance companies, hedge funds) and global exchanges; the firm acts as a liquidity provider on over 200 electronic exchanges.
- **Mission or purpose statement**: “Solving the puzzle of global markets” — a research-driven approach to trading, blending human intuition with cutting-edge quantitative analysis.

## Products & Services
- **Market Making**: Jane Street provides continuous, two-sided quotes on equities, ETFs, bonds, options, and other instruments, helping keep prices consistent and reliable across global markets.
- **Proprietary Trading**: The firm trades its own capital across a wide range of asset classes, using sophisticated models and automated strategies.
- **Institutional Sales & Trading**: Partners with asset managers, pensions, and insurance companies to provide trading solutions and access to differentiated liquidity.
- **Technology & Infrastructure**: Builds all critical software in-house (trading systems, risk management, data analysis tools), using the OCaml functional programming language.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private firm). Industry estimates suggest Jane Street is one of the world’s largest and most profitable market makers, with annual trading volumes in the trillions of dollars.
- **Key Metric**: Not publicly disclosed. The firm is widely reported to have generated billions in annual revenue and profit, though exact figures are private.
- **Notable Investors/Partners**: 100% employee-owned. No external investors. Partners include top institutional clients globally.
- **Growth Signals**: Jane Street has grown every year in team, capital, and global presence since its founding in 2000. It has expanded from a focus on ETFs into equities, bonds, options, and other asset classes. The firm continues to invest heavily in machine learning and quantitative research.

## Competitive Advantages
- **Technical Moat**: Builds almost all software in-house using OCaml, a statically typed functional language that provides high reliability, real-time visibility, and performance at market scale.
- **Data & Scale**: Trades on 200+ electronic exchanges globally, processing trillions of historical events to uncover both sub-microsecond and long-term market inefficiencies.
- **Talent Density**: A culture of intellectual curiosity and collaboration across trading, research, and technology teams. The firm is known for hiring top minds from any background (math, physics, CS, engineering) and training them in-house.
- **Long-Term Track Record**: Over 20 years of consistent growth and profitability, navigating volatile markets with a disciplined, research-driven approach.

## Strategic Focus
- **Machine Learning & Quantitative Research**: Deepening the use of ML techniques across all trading strategies, from high-frequency to long-term systematic models.
- **Global Expansion**: Continuing to grow its presence in existing offices (NY, London, HK, Singapore, Amsterdam) and exploring new markets.
- **Technology Investment**: Ongoing investment in infrastructure, hardware (e.g., programmable hardware, high-performance computing), and software tools to maintain a competitive edge.
- **Talent Pipeline**: Heavy focus on recruiting interns and new grads, as well as experienced hires, with structured programs for learning and mentorship.

## Why Work Here
- **Culture**: Described as “open and collaborative,” with porous boundaries between trading, research, and technology. Intellectual humility and curiosity are highly valued.
- **Learning & Development**: Offers immersive internships, multi-day programs, direct mentorship, and a week abroad for interns. Full-time employees have access to extensive internal training, a library, and classrooms in every office.
- **Work Environment**: Most employees write code as part of their regular work. The firm is known for its technical excellence and for using the most advanced tools available.
- **Benefits**: Daily breakfast and lunch, fully-stocked kitchens, on-site gyms, nursing suites, quiet rooms, recreation spaces, health services, and more. Offices are designed for collaboration and deep focus.
- **Remote/Hybrid Policy**: Not explicitly stated, but the firm emphasizes in-person collaboration on trading floors. Offices are located in major global cities.
- **Diversity**: Actively seeks people from all backgrounds and emphasizes that the company is only as strong as its people.

## Sources
1. [janestreet.com - Home](https://www.janestreet.com/)
2. [janestreet.com - Overview](https://www.janestreet.com/join-jane-street/overview/)
3. [janestreet.com - What We Do](https://www.janestreet.com/what-we-do/overview/)
4. [janestreet.com - Departments](https://www.janestreet.com/join-jane-street/departments)
5. [janestreet.com - Open Roles](https://www.janestreet.com/join-jane-street/open-roles/)

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