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Software Engineer, Infrastructure

Thinking Machines Lab · San Francisco, California

Location
San Francisco, California, United States
Employment
Full time
Level
Mid level
Posted
Yesterday

About this role

About Thinking Machines

The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.

About the Role

We're hiring a Software Engineer, Infrastructure to design and build the distributed systems that power our model training and serving platforms. You'll work on the systems underlying everything we do - from the clusters that train our frontier models with Inkling, to the multi-tenant serving infrastructure behind Tinker.

This is a foundational infrastructure role at a fast-moving startup. You'll have real ownership over systems that run at large scale, and your work will directly determine how quickly our research and product teams can iterate.

What You'll Do

  • Design, build, and operate distributed systems that support large-scale model training and inference across thousands of accelerators

  • Build and maintain core infrastructure, including orchestration, scheduling, storage, and resource management systems

  • Improve the reliability, performance, and observability of infrastructure used across research and product teams

  • Partner with researchers and platform engineers to understand infrastructure needs and turn them into robust, well-abstracted systems

  • Debug and resolve complex distributed failures across the stack, from networking and storage to compute and scheduling

  • Write and maintain internal libraries and APIs, primarily in Python and Go, that other engineers build on

Skills & Qualifications

Minimum Qualifications

  • Demonstrated expertise designing and developing large-scale distributed systems

  • Strong proficiency in Python and Go

  • Experience building, deploying, and operating production infrastructure at scale

  • Solid grounding in distributed systems fundamentals, such as consensus, consistency, fault tolerance, and networking

Preferred Qualifications

  • Experience with ML infrastructure, such as training orchestration, job schedulers, or distributed storage and data systems

  • Experience operating large-scale GPU or TPU clusters

  • Experience with container orchestration (e.g. Kubernetes) and infrastructure-as-code

  • Contributions to open-source infrastructure projects

  • Comfortable working with high autonomy in a fast-changing, early-stage environment

Logistics

  • Location: This role is based in San Francisco, CA.

  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $400,000 USD.

  • Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.

  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

As published by Thinking Machines Lab. Applications are handled on their site.

Skills this posting mentions

GPUInfrastructureKubernetes

About Thinking Machines Lab

Thinking Machines Lab is an artificial intelligence research and product company. We’re building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.

All 55 openings at Thinking Machines Lab

One click, then it is written

Apply to Thinking Machines Lab with a resume written for this role.

Queue Software Engineer, Infrastructure and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Thinking Machines Lab’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

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Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board Thinking Machines Lab publishes. Refolk is not the employer and does not handle their hiring. Applications go to Thinking Machines Lab directly.