GPU Systems Engineer - HPC / Parallel Computing

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 small, growing, and highly motivated team dedicated to an ambitious technical plan. We operate with a flat mobile organizational structure where everyone contributes 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 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. Employment Details 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). Annual Salary Range $160,000 – $320,000 + equity + benefits. 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. #J-18808-Ljbffr Vast.ai