Generalist Infrastructure and Systems Engineer (Distributed Systems & AI Infrastructure)

thinking machines lab San Francisco Bay Area
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AI Summary

Join a small, high-impact team responsible for architecting and scaling the core infrastructure behind our foundation models and AI products. You will work across the full technical stack, solving complex distributed systems problems and building robust, scalable platforms. This role requires proficiency in Python or Rust, experience with large-scale clusters and container orchestration, and a bias for action in a collaborative environment.

Key Highlights
Work directly with researchers to accelerate experiments and improve infrastructure efficiency.
Contribute to core infrastructure, data infrastructure, or developer productivity teams.
Build and run large Kubernetes clusters with GPU workloads, design data pipelines with Spark, and develop tooling for optimized developer environments.
Key Responsibilities
Architect and scale the core infrastructure behind everything we do.
Work across the full technical stack, solving complex distributed systems problems.
Build robust, scalable platforms.
Work directly with researchers to accelerate experiments and improve infrastructure efficiency.
Support teams that train, research, and ultimately serve AI models.
Build the underlying infrastructure for clusters to reliably and safely train frontier models.
Build and maintain data systems for research and products.
Design and optimize data pipelines using tools like Spark.
Build scalable, reliable data infrastructure while embedding governance best practices.
Build tooling, systems, frameworks, and systems to ensure well-configured, optimized developer environments.
Technical Skills Required
Python Rust Kubernetes Slurm Spark Containers CI
Benefits & Perks
Annual salary range: $350,000 - $475,000 USD
Generous health, dental, and vision benefits
Unlimited PTO
Paid parental leave
Relocation support as needed
Visa sponsorship
Nice to Have
Strong debugging across application, OS, and network layers.
Proficiency in Python or Rust (or similar), containers, and modern CI.
Experience with Kubernetes, controllers/operators, or performance profiling.
Familiarity with GPU/ML workflows or large-scale data/eval pipelines.

Job Description


Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.


We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.


About the Role

We’re looking for generalist infrastructure and systems engineers to help build the systems that power our foundation models and the internal teams on research and product development to be able to create the models and ship the products powered by our models.


You'll join a small, high-impact team responsible for architecting and scaling the core infrastructure behind everything we do. You’ll work across the full technical stack, solving complex distributed systems problems and building robust, scalable platforms.


Infrastructure is critical to us: it's the bedrock that enables every breakthrough. You'll work directly with researchers to accelerate experiments, improve infrastructure efficiency, and enable key insights across our models, products, and data assets.


What You’ll Do

We interview generally, but during project selection we’ll take into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the infrastructure teams where they'll have the greatest impact and growth potential.


Here are example areas you may contribute to depending on your area of expertise and interest:

  • Core Infrastructure: We support teams that train, research, and ultimately serve AI models and build the underlying infrastructure for the clusters to reliably and safely train frontier models. Examples might include building systems and running large Kubernetes clusters with GPU workloads, or building infrastructure to support Tinker.
  • Data Infrastructure: We build and maintain the data systems for our research and products. You'll design and optimize data pipelines using tools like Spark and other modern data infrastructure technologies. You’ll build scalable, reliable, data infrastructure while embedding governance best practices.
  • Developer Productivity: We care deeply about research and engineering productivity and our ability to continue shipping quickly. We build tooling, systems, frameworks, and systems to make sure everyone gets well configured, optimized developer environments.


Skills and Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
  • Proficiency in at least one backend language (we use Python or Rust).
  • Experience operating large‑scale clusters and container orchestration systems (e.g. Kubernetes or Slurm).
  • Comfort operating across the stack and owning projects end-to-end.
  • Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
  • A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.


Preferred qualifications — we encourage you to apply if you meet some but not all of these:

  • Strong debugging across application, OS, and network layers.
  • Proficiency in Python or Rust (or similar), containers, and modern CI.
  • Experience with Kubernetes, controllers/operators, or performance profiling.
  • Familiarity with GPU/ML workflows or large‑scale data/eval pipelines.


Logistics

  • Location: This role is based in San Francisco, California.
  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 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 set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.


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