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Thinking Machines Lab

Researches AI and builds tools to customize models

Software Engineer - Sandboxing

Platform EngineeringConfirmed live in the last 24 hours
Full-time$300k - $400k /yrIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent experience in computer science, engineering, or a similar field.
  • Proficiency in at least one backend language, such as Python or Rust.
  • Experience building or operating isolation or virtualization technology, such as containers, micro-virtual machines (e.g., Firecracker or Cloud Hypervisor), or sandboxed runtimes (e.g., gVisor or Kata Containers).
  • A solid grounding in Linux internals relevant to isolation, including namespaces, control groups (cgroups), seccomp, capabilities, and networking.
  • Ability to operate across the stack and own projects end-to-end.
  • Ability to work in a highly collaborative environment involving cross-functional partners and subject matter experts.

Responsibilities

  • Design, build, and operate sandboxed execution environments for running untrusted, model-generated code and tool calls at scale.
  • Improve isolation boundaries using technologies such as containers, micro-virtual machines, or gVisor-style kernels, balancing security against startup latency and throughput.
  • Build scheduling, resource-management, and lifecycle systems that provision, reuse, and tear down sandboxes efficiently under heavy concurrent load.
  • Partner with researchers and the product team to expose sandboxing primitives that are simple to use and difficult to misuse.
  • Instrument sandboxes for observability and abuse detection, and respond to novel escape or exploitation attempts as they are discovered.
  • Own the reliability and performance of the sandboxing platform end-to-end, from API design to the underlying virtualization layer.

Desired Qualifications

  • Experience securing systems that execute untrusted or adversarial code, including threat modeling and hardening against sandbox escapes.
  • Familiarity with running large-scale, multi-tenant infrastructure on Kubernetes or similar orchestration systems.
  • Experience with performance-sensitive systems programming and reducing cold-start latency for ephemeral compute.
  • A track record of contributing to open-source infrastructure or security tooling.
  • Interest in how AI agents use tools and code execution, and how that shapes the design of safe execution environments.

About the Company

Thinking Machines Lab

Researches AI and builds tools to customize models

Thinking Machines Lab researches and builds AI systems, aiming to make AI more widely understood, customizable, and capable. It publishes much of its research openly on its Connectionism blog, starting with work on making AI models give consistent answers to the same question. Its first product, Tinker, lets researchers and developers fine-tune open-weight AI models on their own data while Thinking Machines runs the computing clusters behind it, so customers focus on their data and training methods instead of managing hardware and pay for the computing they use. Former OpenAI chief technology officer Mira Murati founded the lab in 2025, and it is based in San Francisco.

Company size
201-500
Company stage
Series A
Total funding
$7B
Headquarters
San Francisco, CA
Founded
2024

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