Member of Technical Staff

Role details

ABOUT THE ROLE Join a small team building AI infrastructure that improves the performance and efficiency of open-source model inference. You will work across models, serving systems, kernels, and production infrastructure to help deliver reliable, cost-effective inference across diverse hardware. WHAT YOU'LL DO - Deliver day-zero support for new open-source models, tuning them for latency and throughput. - Optimize serving systems through techniques such as batching, KV caching, speculative decoding, and quantization. - Write and tune kernels using CUDA, HIP, and Triton across a range of accelerator platforms. - Design, deploy, and operate heterogeneous clusters across infrastructure providers. - Run production inference across mixed hardware fleets, improving reliability, observability, and cost per token. - Work with customers as well as the engineering team to identify problems and guide solutions. WHAT WE'RE LOOKING FOR - One to six years of experience, with strong systems, backend, infrastructure, or low-level engineering work. - Strong understanding of computer architecture, memory hierarchies, and operating system internals. - Experience owning complex systems end to end, notable technical achievements, or a record of rapid progression. - Strong undergraduate computer science fundamentals and experience at a high-caliber technology organization or early-stage startup. - Familiarity with CUDA, HIP, Triton, Python, or GPU programming; experience with inference optimization and large-scale infrastructure is valuable. - Experience using AI agents and coding tools to improve engineering workflows, and comfort communicating with customers. - Available to start immediately and work on-site in San Francisco. COMPENSATION & BENEFITS Base salary is $200,000 to $300,000 USD annually. Visa sponsorship is available. LOCATION On-site in San Francisco, California, United States.