GPU Systems Engineer – HPC / Parallel Computing
Vast.ai · Los Angeles, CA · 1 mo ago
On-siteInformation Technology$160k–$320k/yrFull-time
About The Role
We're looking for a systems engineer with HPC or parallel programming experience to help scale AI inference. You'll leverage your knowledge of high-performance systems to optimize GPU performance at the bleeding edge of AI.
Location
On-site at our office in San Francisco or Westwood, Los Angeles.
Tech Stack
- CUDA/C++
- GPGPU
- Python
- Linux
Key Responsibilities
- Design and optimize GPU kernels and tensor libraries
- Translate HPC techniques into scalable AI inference solutions
- Evaluate emerging architectures and resource management approaches
- Collaborate with technical leadership to improve GPU infrastructure efficiency
Ideal Experience
- Advanced C++ (C++17/20 preferred)
- Expertise with at least one parallel framework (CUDA, HIP, SYCL, OpenCL, OpenACC, or similar)
- Strong background in systems optimization and HPC performance tooling
- Familiarity with distributed training/inference frameworks (bonus)
Interview Process
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
- Initial screening (virtual, 15 minutes)
- Quick dive into Vast, systems and architectures (virtual, 30 minutes)
- LLM-assisted coding assessment (virtual, 1 hour)
- Meet and greet with coding assessment (on-site, 2 hours)
Our goal is to complete the interview process in two weeks.
Benefits
- Comprehensive health, dental, vision, and life insurance
- 401(k) with company match
- Meaningful early-stage equity
- Onsite meals, snacks, and close collaboration with founders/tech leaders
- Ambitious, fast-paced startup culture where initiative is rewarded
Pay
Compensation Range: $160K - $320K