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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 small, growing, and highly motivated team dedicated to an ambitious technical plan. We operate with a flat mobile organizational structure where all contribute directly to the company’s mission. Leadership is earned by those who show initiative and deliver excellence.
We seek engineers/researchers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of excellent research, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
About the RoleWe’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
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
- 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)
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)
$160,000 – $320,000 + equity + benefits
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
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
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
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- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
