Energy Jobline ZR
GPU Systems Engineer - HPC / Parallel Computing in San Francisco
Energy Jobline ZR, San Francisco, California, United States, 94199
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.
LOCATION: On‑site at our office in San Francisco or Westwood, Los Angeles.
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)
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.
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
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
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LOCATION: On‑site at our office in San Francisco or Westwood, Los Angeles.
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)
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.
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
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
#J-18808-Ljbffr