Hudson River Trading
GPU Systems Engineer
$150K–$300K
Austin, TX, United States +5 · Full-time · Posted Sep 25, 2025
- Location
- Austin, TX, United States
Chicago, Illinois, United States
London, United Kingdom
New York, NY, United States
Norway
All Offices - Experience
- 5+ years.
About the job
Design, operate, and optimize large-scale distributed GPU infrastructure supporting HPC and AI research workloads.
What you'll do
- Build and optimize distributed GPU compute clusters; diagnose performance bottlenecks across compute, storage, and networking.
- Profile, benchmark, and tune GPU workloads with research and development teams.
- Automate deployment, monitoring, and troubleshooting across thousands of nodes; own infrastructure projects and support hardware and software deployment.
What they ask for
- 5+ years of large-scale Linux systems engineering experience in HPC, AI, or distributed infrastructure.
- Extensive Linux installation, performance tuning, and troubleshooting experience; expertise troubleshooting distributed GPU workloads and GPU performance.
- Proficiency in Python scripting and automation frameworks.
- Experience with NVIDIA technologies beyond CUDA, such as NCCL, GPUDirect RDMA, and NVLink.
Nice to have
- CUDA or C/C++ experience.
- Familiarity with configuration management tools such as Salt, Ansible, Puppet, or Chef.
Pay
150,000 to 300,000 USD per year (base salary)
Tools
Linux, Python, CUDA, C/C++, NCCL, GPUDirect RDMA, NVLink, Salt
AI focus
Supports HPC/AI research infrastructure and profiles, benchmarks, and fine-tunes GPU-based workloads.
Model-written summary · the original posting is authoritative