Our Machine Learning Engineering Internship is designed to give you a real sense of what it’s like to work at Jane Street full-time as a Machine Learning Engineer. Over the course of your program, you will explore ways to approach and solve cutting-edge ML problems through fun and challenging classes, interactive sessions, and group discussions—and then you will have the chance to put those lessons to practical use. Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.
You will be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done. When you’re not working on your project, you will have plenty of time to enjoy our office amenities, explore our physical and virtual educational resources, attend guest speakers and social events, and engage with the parts of our work that excite you the most.
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. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you’ll fit right in.
Learn more about Jane Street’s internship program here.
About the PositionMachine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. If you’d like to learn more, you can have a look at our Machine Learning page.
During the program, you’ll work on projects mentored closely by the full-time employees who designed them. Some projects consider big-picture questions that we’re still trying to figure out, while others involve building something new. You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.
The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including one dedicated to assessing ML engineering skills.
About YouWe don’t expect you to have a background in finance—we’re more interested in how you think and learn than what you currently know. You should be:
- An undergraduate or PhD student with practical experience training an ML model, working on an ML library, or optimizing an ML workflow
- A top-notch programmer with a love for technology
- Intellectually curious, collaborative, and eager to learn
- Humble and unafraid to ask questions and admit mistakes
If you're a recruiting agency and want to partner with us, please reach out to [email protected].
Top Skills
What We Do
Jane Street works differently. As a liquidity provider and market maker, we trade on more than 200 trading venues across 45 countries and help form the backbone of global markets. Our approach is rooted in technology and rigorous quantitative analysis, but our success is driven by our people.
Our bright, beautiful offices in the heart of New York, London, Hong Kong, and Amsterdam are open and buzzing with conversation. We come from many backgrounds and encourage travel between offices to share perspectives. Some of our best ideas come from bumping into a visiting colleague at the office coffee bar.
Markets move fast. Staying competitive as we’ve grown has required constant invention—of new trading strategies, technology, and processes. We’ve found this is easier when you hire humble, kind people. They tend to help each other, and prioritize teamwork over titles.
We invest heavily in teaching and training. There’s a library and a classroom in every office, because deepening your understanding of something is considered real work. Guest lectures, classes, and conferences round out the intellectual exchanges that happen every day.
People grow into long careers at Jane Street because there are always new and interesting problems to solve, systems to build, and theories to test. More than twenty years after our founding, it still feels like we’re just getting started.
