Thunder Compute
This role focuses on building the core C++ systems behind a GPU virtualization layer, involving low-latency performance optimization, distributed systems debugging, and production reliability. The engineer will take ownership of complex systems from early experimentation through production deployment, addressing challenges like remote CUDA operation latency and high-performance networking. The position requires exceptional low-level engineering talent and a strong work ethic to deliver high-quality, reliable systems code.
Headquarters
San Francisco, California, United States
Company Size
1-10 employees
Founded
2024
Thunder Compute is a GPU cloud platform that offers one‑click, pay‑as‑you‑go GPU instances (H100, A100 80GB, RTX A6000) at up to ~80% lower cost than major clouds — H100s from $1.38/hr, A100s from $0.78/hr, A6000s from $0.27/hr. Users can launch instances in seconds via the web console, CLI, or VS Code extension and connect over SSH, Jupyter, or directly in their editor, with fast SSD storage and high‑bandwidth networking for modern ML workloads. There are no long‑term contracts or minimums, making it suitable for AI startups, researchers, indie developers, and students who need affordable training, fine‑tuning, and inference compute. The platform also includes org controls and modern security/authentication features to support teams and enterprise use.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Thunder Compute.
116% above the average for this role