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Adaption Labs

AI research startup pursuing continual adaptation

Inference Engineer

Applied Machine LearningUpdated on Nov 11
Full-timeSan Francisco, CA, USANo salary listed

About the Job

Requirements

  • At least 5 years of experience in machine-learning 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.
  • Strong Python skills and proficiency in C++, Rust, or another systems language.
  • Experience with GPU performance, including CUDA, NCCL, mixed precision, memory layout, kernels, or quantization.

Responsibilities

  • 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 the company’s infrastructure and external providers based on cost, capacity, and performance.
  • Work within serving engines such as vLLM, SGLang, and TensorRT-LLM, going below the framework when needed.
  • Build profiling and measurement systems that show where time, memory, and compute are being spent.
  • Own the cost and performance of the inference stack, improving efficiency as workloads, traffic, and hardware change.

About the Company

Adaption Labs

AI research startup pursuing continual adaptation

Adaption Labs builds AI systems that learn from real-world interactions instead of relying on ever-larger language models. Their products aim for continual, real-time adaptation so AI can improve while being cost-efficient and secure, without full retraining. The company works toward flexible, personalized, and accessible AI that can adapt to specific enterprise workflows, reducing the need for massive data centers and helping more organizations participate in AI development. Unlike models that depend mainly on scaling compute, Adaption Labs focuses on efficient learning from experience to provide practical, enterprise-ready AI that evolves over time.

Company size
11-50
Company stage
Seed
Total funding
$50M
Headquarters
San Francisco, CA
Founded
2025

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