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Software Engineer, Infrastructure

Thinking Machines LabSoftware
Pay
$300K–$350K
per year
Work mode
On-site
Full Time
Level
Mid

San Francisco, CA at a glance

Rent
#2 of 51
$2,680/mo+46% vs US avg
Weather
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295 mild days0 hot · 0 cold
Income tax
#1 of 51
13.3% top rateCalifornia

What you need

  • Expertise in large-scale distributed systems design
  • Strong proficiency in Python and Go
  • Production infrastructure operation at scale
  • Distributed systems fundamentals: consensus, fault tolerance
  • ML infrastructure experience (training orchestration, schedulers)

What you'll do

  • Design and operate distributed systems for model training/inference
  • Build core infrastructure: orchestration, scheduling, storage
  • Improve reliability, performance, observability of infrastructure
  • Partner with researchers to translate needs into robust systems
  • Debug complex distributed failures across full stack

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 - $350,000 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.

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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.

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