Apply Now

Machine Learning Performance Engineer

• Posted 5 days ago • Updated 5 days ago

Full Time

On-site

Fitment

Dice Job Match Score™

📋 Comparing job requirements...

Job Details

Skills

Trading
Real-time
Research
Data Storage
Data Link Layer
Caching
Value Engineering
Finance
Machine Learning (ML)
Sass
Debugging
GDB
CUDA
InfiniBand
Optimization
Computer Networking
Algorithms
GPU
Training
MPI
Recruiting

Summary

{"description": "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 ", "salary_raw": "Row(double=None, string=None)"}

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 90922487
Position Id: 24168514
Posted 5 days ago

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

Similar Jobs

Principal Machine Learning Engineer

New York, New York

•

Today

{"description": " About the Role A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time. As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. You operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution

Full-time

Staff Machine Learning Engineer

New York, New York

•

22d ago

{"description": " About the Role A1 is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. As Technical Lead, Mach

Full-time

Machine Learning Engineer

New York, New York

•

5d ago

{"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 l

Full-time

Senior Machine Learning Engineer

New York, New York

•

5d ago

Full-time

Search all similar jobs