GPU Systems Engineer - HPC / Parallel Computing
- Location
- San Francisco, CA · On-site
- Job type
- Full-time
- Level
- Senior
- Listed
- 22 days ago
Skills & highlights for this role
- CUDA
- C++
- GPU kernel optimization
- HPC performance tooling
- Linux
Also useful
- HIP
- SYCL
- OpenCL
- distributed training frameworks
Stated benefits & perks
- Health
- Dental
- Vision
- Life insurance
- 401k match
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:
- 15 min - Initial screening (virtual)
- 45 min - Quick dive into Vast, work history (virtual)
- 45 min - Systems and architectures (virtual)
- 1 hour - LLM-assisted coding assessment (virtual)
- 2 hours - Meet and greet with coding assessment (on-site)
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
About US
Vast.ai 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.
From Vast.ai's careers page, first listed on Rolev.ai on October 17, 2026. Rolev.ai is not the employer.
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Common questions
Where is the GPU Systems Engineer - HPC / Parallel Computing job at Vast.ai located?
This GPU Systems Engineer - HPC / Parallel Computing position at Vast.ai is located in San Francisco, CA (On-site). Always check Vast.ai's application page for specific state eligibility or relocation policies.
What qualifications are required for GPU Systems Engineer - HPC / Parallel Computing at Vast.ai?
For the GPU Systems Engineer - HPC / Parallel Computing role, Vast.ai highlights experience with CUDA, C++, GPU kernel optimization, HPC performance tooling, Linux. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the GPU Systems Engineer - HPC / Parallel Computing position at Vast.ai?
This listing links directly to Vast.ai's Ashby application page. You can apply directly on Vast.ai's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.