Software Engineer, Infrastructure

Thinking Machines Lab

• $300K — $400K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Expertise in designing and developing large-scale distributed systems
  • Proficient in Python and Go programming languages
  • Experience in building and operating production infrastructure at scale
  • Strong understanding of distributed systems fundamentals like consensus and fault tolerance
  • Preferred experience with ML infrastructure and job schedulers
  • Familiarity with container orchestration tools like Kubernetes
  • Comfortable in a fast-paced, early-stage startup environment

Responsibilities

  • Design and operate distributed systems for large-scale model training and inference
  • Build and maintain core infrastructure components like orchestration and resource management
  • Enhance reliability, performance, and observability of infrastructure
  • Collaborate with researchers to translate infrastructure needs into robust systems
  • Debug complex distributed failures across various system layers
  • Develop and maintain internal libraries and APIs for engineering teams

Benefits

  • Generous health, dental, and vision benefits
  • Unlimited paid time off (PTO)
  • Paid parental leave
  • Relocation support as needed
Full Job Description
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.

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