Jane Street
We are looking for an engineer with experience in low-level systems programming and optimization to join our growing ML team.
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.
Your part here is optimizing the performance of our models – both training and inference. We care about efficient large-scale training, low-latency inference in real-time systems, and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking, and host- and GPU-level considerations. Zooming in, we also want to ensure our platform makes sense even at the lowest level – is all that throughput actually goodput? Does loading that vector from the L2 cache really take that long?
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 and a passion for solving interesting problems, we have a feeling you’ll fit right in.
There’s no fixed set of skills, but here are some of the things we’re looking for:
- An understanding of modern ML techniques and toolsets
- The experience and systems knowledge required to debug a training run’s performance end to end
- Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores, and the memory hierarchy
- Debugging and optimization experience using tools like CUDA GDB, NSight Systems, NSight Compute
- Library knowledge of Triton, CUTLASS, CUB, Thrust, cuDNN, and cuBLAS
- Intuition about the latency and throughput characteristics of CUDA graph launch, tensor core arithmetic, warp-level synchronization, and asynchronous memory loads
- Background in Infiniband, RoCE, GPUDirect, PXN, rail optimization, and NVLink, and how to use these networking technologies to link up GPU clusters
- An understanding of the collective algorithms supporting distributed GPU training in NCCL or MPI
- 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.
To apply for this job please visit job-boards.greenhouse.io.
Explore Jane Street online
Working in New York, NY
New York, often called New York City (NYC), is the most populous city in the United States. It is located at the southern tip of New York State on New York Harbor, one of the world's largest natural harbors. The city comprises five boroughs—Manhattan, Brooklyn, Queens, the Bronx, and Staten Island; each is coextensive with its respective county. It is the geographical and demographic center of both the Northeast megalopolis and the New York metropolitan area, the largest metropolitan area in the United States by both population and urban area. New York is a global center of finance and commerc
Market context
- Similar listings in New York, New York, United States 2
Job details above are provided by the employer/source. The sections on this page are compiled from public data sources with AI assistance.
Accommodations: if you need a workplace accommodation to apply for or perform this job, see ADA.gov or EEOC.gov for guidance on your rights and how to request one.
Keep exploring on Get A Job.ai
Not quite the right fit? Your next opportunity is a click away.
- Browse all jobs
- More jobs by category
- Remote jobs you can do from anywhere
- Research typical pay for this role
- Set a job alert so new matches reach you first
- Upload your resume to apply faster
Hiring instead? Post a job and reach candidates searching right now.