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adaption
adaption
1 – 10 Employees
ConsultingLogisticsMarketing
adaption develops adaptive AI systems and tooling designed to tailor intelligence to individual users, languages, industries, and specialized edge cases. Its work spans Adaptive Data, Adaptive Intelligence, and Adaptive Interfaces—approaches that help models adjust continuously and support more responsive user experiences without relying as heavily on manual prompting or a single monolithic model. The company’s technology is relevant to organizations exploring practical AI applications across areas such as consulting, logistics, and marketing.
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Inference Engineer — Adaption (Hybrid, Bay Area)

Optimize inference infrastructure for throughput, cost, and latency at Adaption, an AI company developing adaptive intelligence systems. Improve model serving across GPUs, inference engines, and production workloads.

USUnited StatesCACaliforniaHybridFull-timeMiddleSeniorEnglish RequiredEngineer
C++PythonRust

Description

  • Lead ownership of inference-stack cost and performance.
  • Increase throughput and reduce cost and tail latency through KV-cache management, continuous batching, speculative decoding, and quantization.
  • Optimize long-context prefill and decode workloads against real production traffic.
  • Adjust routing between internal infrastructure and external providers according to cost, capacity, and performance.
  • Use serving engines including vLLM, SGLang, and TensorRT-LLM, working beneath the framework when necessary.
  • Develop profiling and measurement systems to locate time, memory, and compute usage.
  • Partner closely with engineers responsible for the serving fleet.

Requirements

  • Bring at least five years of experience in ML systems, inference infrastructure, or performance engineering, with measurable gains in cost or latency.
  • Demonstrate deep knowledge of model serving, including prefill and decode, memory bandwidth, batching, and concurrency.
  • Have production experience with serving engines such as vLLM, SGLang, or TensorRT-LLM.
  • Use Python confidently and be proficient in C++, Rust, or another systems programming language.
  • Understand GPU performance topics including CUDA, NCCL, mixed precision, memory layout, kernels, or quantization.
  • Be able to work in person in the Bay Area within a hybrid setup.

Benefits

  • Combine in-person Bay Area collaboration with a distributed, global-first team and team offsites.
  • Receive an annual Adaption Passport travel stipend for exploring a country you have not previously visited.
  • Get a weekly allowance for takeout meals or grocery delivery.
  • Access comprehensive medical coverage and generous paid time off.

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