Vast.ai logo

GPU Systems Engineer – HPC / Parallel Computing

Vast.ai

San Francisco, CAFull-time$160–320K/yrPosted 3mo agoStill listed 2 days ago

Most applications go out cold — see where you stand first. No sign-up to start.

Watch jobs like this.

At a glance

Compensation
$160–320K/yr
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Vast.ai is seeking a GPU Systems Engineer to design and optimize GPU kernels and tensor libraries for high‑performance AI inference. The role involves translating HPC techniques into scalable solutions, evaluating emerging architectures, and collaborating with technical leadership to improve GPU infrastructure efficiency. Candidates should have strong C++ skills, experience with parallel frameworks, and a background in systems optimization.

Skills & qualifications

RequiredNice to have

Skills

CUDAC++GPGPUPythonLinuxHPCParallel FrameworksDistributed Training

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match

Full job description

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:

  • 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

Similar jobs, posted recently

Open roles like this one, listed in the last 30 days.

You've read the whole posting — now see how you match it.