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Sail Research

Open-source AI inference for autonomous agents

Member of Technical Staff - Inference

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$200k - $300k /yr

About the Job

Requirements

  • Strong understanding of core large language model mechanics, including key-value cache, mixture-of-experts, and prefill versus decode phases.
  • Interest in machine learning systems research and following research such as speculative decoding and sparse attention.
  • Familiarity with modern tile-based GPU programming, such as Triton, CUTLASS, or ThunderKittens, or interest in learning these technologies.

Responsibilities

  • Modify and extend state-of-the-art inference engines such as vLLM and SGLang, and work on Sail's internal engine.
  • Analyze GPU time spent during a forward pass and explain kernel launches using an nsys profile.
  • Design and implement parallelism schemes for varied hardware topologies.
  • Write and debug GPU kernels for specific workloads, such as cascade attention.
  • Develop request scheduling strategies, improve communication and computation overlap, investigate approaches to increase cache hit rates, and identify better methods to benchmark inference performance.

About the Company

Sail Research

Open-source AI inference for autonomous agents

Sail Research provides AI inference services for open-source models at scale to power autonomous background agents. It offers a private-beta OpenAI-compatible API that supports open models like Deepseek, Kimi, and Qwen, plus fine-tuned versions, enabling token-serving for customers. It handles end-to-end work, including CUDA GPU optimization, tweaking inference engines, and distributing workloads across multiple providers with spot compute to reduce costs. Its goal is to help autonomous agents make meaningful independent progress on complex problems by delivering reliable, scalable, and affordable open-model inference through an OpenAI-compatible API.

Company size
11-50
Company stage
Series A
Total funding
$80M
Headquarters
San Francisco, CA
Founded
2026

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