Jane Street
ApplyFrontier Research for Quantitative Trading
We're building a truly AI-driven trading firm, rooted in frontier research and deep market expertise. You'll join a close-knit group of brilliant, supportive colleagues, harnessing tens of thousands of GPUs, petabytes of training data, and billions in trading capital. If sharing ideas in a high trust environment with lots of autonomy and minimal hierarchy sounds good to you, reach out!
Machine Learning/Trading/Quantitative Research
On our Machine Learning team, you'll build the deep learning models that power our trading strategies, supported by thousands of high-end GPUs. Financial markets pose unique challenges for machine learning: extreme noise, nonstationarity, and a competitive multi-agent environment. Our researchers have to be up on the latest developments in the field, as well as pursuing novel techniques.
Our ML researchers and engineers work across a range of timescales and problem types, from probing microstructure dynamics at sub-microsecond resolution to uncovering persistent inefficiencies buried in trillions of historical events. Research systems must support constant development and innovation, and trading systems must perform inference and execute trades at blistering speeds.
Traders wear a lot of hats: they build machine learning models, analyze market dynamics and risk, seek out new businesses, identify what to optimize or automate next. Most of Jane Street's trading is fully automated, though some opportunities still call for rapid human decision-making.
A Culture of Problem Solving
At Jane Street, puzzles aren't just a pastime. We find puzzles to solve in everything we do, from building models for machine learning to analyzing complex trading scenarios. Of course, we do puzzles for fun too! Here are a few examples of the kinds of problems we love, and you can find more on our puzzles page.
Your Career at Jane Street
Roles at Jane Street are flexible and tailored to your strengths. You can be a trader who writes code, an engineer who builds models, or a researcher who interacts with markets in real time. There are no titles and minimal hierarchy, which means your career trajectory is responsive to your interests and abilities.
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're curious and passionate about solving interesting problems, you'll fit right in.
Technology
Jane Street's Technology team creates the infrastructure that keeps us growing: our globe-spanning data network and compute environment, the platforms that power trading, the systems that manage our billions of trades per day. The team draws people with backgrounds in machine learning, programmable hardware, systems administration, network engineering, compiler design, and beyond.
We look for smart people with curious minds from any background
Learn more about who we are, where we're hiring, what it's like to work here, and what we offer our employees. When you're ready, take a look at our open roles.
Testimonials
There's nothing in the open literature that is close to what we are doing. When you do find things that work, you really do feel that you're actually on the frontier—you might be the first person in the world to figure these things out.
— Fan Pu, Machine Learning
Everybody here is a math nerd. If you go up to someone and start explaining an interesting math puzzle—the first thing they'll do is stop you before you can tell them how to solve the puzzle because they want to try it on their own.
— Jane, Trading
Qualities that we really value here at Jane Street are curiosity and humbleness---that allows us to have a very open culture.
— Andreas, Sales & Trading
There's a wide variety of people—from kernel developers thinking about deep technical details for GPU performance, to people who think purely about math and apply that to our machine learning problems.
— Corwin, Machine Learning
Message from Grant
There's one thing that used to surprise me, and even confuse me a little, whenever I'd meet folks from Jane Street, which is how much they all think about education.
Years ago I remember being told about a series of lessons they produced called Real Numbers, teaching foundational topics such as probability. At first, I thought "Huh, that's neat, but kind of a strange thing for such a company to do". Later, I learned that someone I met there had coauthored one of my favorite books introducing contest-style problem-solving when I was younger. Yet another person I met had just returned from a few years' break she had taken from Jane Street to finish her PhD in number theory, simply because that was always something she had deeply valued and loved.
I figured I was probably getting a biased sample, since the people talking to me are likely those who are disproportionately interested in math education. I'm sure that's true, but it's also clearly deeper than education-as-a-side-interest. The offices are full of classrooms, immense amounts of thought go into training and curricula, and the nature of people's roles seems to shift meaningfully over the years, meaning constant training and upskilling. As an outsider looking in, I think this explains a lot about their unusually high retention rate. Smart people like to feel like they're growing, and get antsy when they aren't.
Also, I can't help but speculate that this is a core part of how they've navigated a shift more toward ML research (see the interview we did together). When there's already a strong culture of internal training and curriculum design, navigating a shifting landscape becomes much easier.