Performance Engineer Inference Engine Jobs in San Francisco, CA

We're looking for performance engineers who treat correctness as part of performance.

Role Overview We are looking for a Performance Engineer to make World Labs’ models train and serve as fast as the hardware allows

What You’ll Do Work directly with research scientists and engineers to make new visual models fast and efficient at inference time.

dashboards and capacity planning Requirements 3+ years in performance engineering or ML systems

About the Role We're hiring a Software Engineer, Inference to own the reliability, scale, and efficiency of the systems that serve our models

As a Software Engineer on Inference, you’ll help define Sierra’s inference architecture across both self-hosted models and third-party inference providers

C++ experience is helpful, especially for working near inference engine code, CI build issues, or performance-sensitive systems, but it is not required.

with the product, inference engine, performance, and capacity teams to identify throughput, latency, utilization, and cost wins, then turn those into shipped improvements

Qualifications CUDA + GPU inference optimization vLLM, SGLang, or TensorRT-LLM experience KV caching, paged attention, batching

and enhancing the performance of our AI inference systems.

AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models

Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.

Overview Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and

The toolchains, development environments, and CI/CD that let inference engineers build, test, and ship across every accelerator platform.

You're experienced with modern inference systems like TGI, vLLM, TensorRT-LLM, and Optimum, and comfortable creating custom tooling for testing and optimization