GPU Systems Engineer – HPC / Parallel Computing

Vast.ai Inc.; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Dental

Vision

Life insurance

401(k) match

Equity

Onsite meals

Startup culture

Job summary

Vast.ai Inc. is seeking a systems engineer with HPC or parallel programming experience to help scale AI inference. You will design and optimize GPU kernels and tensor libraries, leveraging CUDA/C++ and related frameworks to push the bleeding edge of AI performance.

This role is based on-site in San Francisco or Los Angeles, with a strong emphasis on HPC techniques and scalable workloads. You will collaborate with technical leadership, evaluate architectures, and contribute to improving GPU

Qualifications

• Advanced C++ skills with modern standards (C++17/20).
• Experience with at least one parallel framework (CUDA, HIP, SYCL, OpenCL, OpenACC).
• Strong background in systems optimization and HPC performance tooling.

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 leadership to improve GPU infrastructure efficiency.

Skills

CUDA/C++

GPGPU

Python

Linux

Advanced C++ (C++17/20)

Parallel frameworks (CUDA, HIP, SYCL, 

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:

• 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