United States
Redwood Materials
True Talent Solutions Partners
Member of Technical Staff
United States
San Francisco, California, United States
Python
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.
- Available to start immediately and work on-site in San Francisco.
- 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.
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.
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