Member of Technical Staff

Role details

ABOUT THE ROLE Join a small AI infrastructure team building efficient inference systems for open-source language models. You will improve performance across diverse hardware, helping make production AI serving faster and more cost-effective. WHAT YOU'LL DO - Bring new open-source models into production with tuning for latency and throughput. - Optimize inference serving, including batching, KV caching, speculative decoding, and quantization. - Write and tune GPU kernels using CUDA, HIP, and Triton across varied accelerator platforms. - Design, deploy, and operate heterogeneous compute clusters across infrastructure vendors. - Run production inference systems, improving reliability, observability, and cost efficiency. - Work with customers to understand needs and help solve infrastructure challenges. WHAT WE'RE LOOKING FOR - Typically 1 to 6 years of experience, with relevant early-career candidates also considered. - Strong systems or infrastructure engineering experience, in addition to any application or full-stack work. - Understanding of computer architecture, memory hierarchy, and operating system internals. - Experience with Python and familiarity with CUDA, HIP, Triton, or other GPU programming tools. - Knowledge of inference optimization techniques such as quantization, batching, KV caching, or speculative decoding. - Experience deploying or operating infrastructure at scale, such as clusters or large GPU fleets, is valuable. - Evidence of taking on challenging systems problems, learning quickly, and using AI coding tools to improve workflows. - Comfort communicating with customers and working across a broad range of technical responsibilities. COMPENSATION & BENEFITS Base salary is $200,000 to $300,000 USD annually. Visa sponsorship is available. LOCATION On-site in San Francisco, California, five days per week.