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Sail Research

Open-source AI inference for autonomous agents

Member of Technical Staff - Sailboxes

Software EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Strong fundamentals in distributed systems, including concurrency, networking, databases, and performance engineering.
  • Experience building and maintaining software for large-scale production distributed systems is preferred rather than required.
  • Experience with cloud infrastructure such as Google Cloud Platform, Amazon Web Services, or Microsoft Azure, container orchestration, and/or multi-cloud networking.
  • Take a product-focused approach to platform work and build solutions that are robust, scalable, and ergonomic for users.

Responsibilities

  • Investigate the custom Firecracker virtual machine fork and improve platform performance.
  • Model historical usage patterns and implement scheduling algorithms that maximize fleet utilization, intelligently autoscale, and minimize latency.
  • Design and implement highly available distributed systems capable of handling millions of operations per second.
  • Build monitoring tools and features for Sailboxes for both human users and agents.
  • Own future product directions for Sailboxes, including Windows and Mac sandboxes and high-efficiency storage.

Desired Qualifications

  • Experience with Firecracker virtual machines.

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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