GPU Systems Engineer – HPC / Parallel Computing
Vast.ai- Location
- San Francisco
- Workplace
- —
- Employment
- Full Time
- Salary
- —
Posted 2mo ago
About Us
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION
On-site at our office in San Francisco or Westwood, Los Angeles.
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.
- Full-Time
- On-site at either our SF or LA offices
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
Skills
- CUDA
- C++
- Python
- Linux
- OpenCL
- LLM
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