Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

ABOUT US

Vast.ai https://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:

- 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