Inference Performance Engineer (Fully Remote)

• Improve throughput, cost, and tail latency through KV-cache management, continuous batching, speculative decoding, and quantization.
• Optimize long-context prefill and decode workloads based on real production traffic.
• Tune routing between infrastructure and external providers based on cost, capacity, and performance.

Qualifications:

• 5+ years in ML systems, inference infrastructure, or performance engineering, with measurable improvements in cost or latency.
• Deep understanding of model serving, including prefill and decode, memory bandwidth, batching, and concurrency.
• Production experience with serving engines such as vLLM, SGLang, or TensorRT-LLM.
• Flexible work with in-person collaboration in the Bay Area and a distributed global-first team.
• Adaption Passport: annual travel stipend to explore a new country.
• Lunch stipend and comprehensive medical benefits with generous paid time off.

Adaption

Adaption builds efficient AI that evolves in real-time, making intelligence flexible, personalized, and accessible to everyone. They focus on talent density, bringing together driven individuals to push the boundaries of continual adaptation.