Software Engineer, Systems Generalist
Thinking Machines Lab3 months ago
Base Salary
$300k - $400k/yr
Responsibilities
- Architect and scale core infrastructure supporting frontier model training, research, model serving, and product development.
- Operate large-scale clusters and container orchestration systems, including GPU workloads on Kubernetes or Slurm.
- Design and optimize scalable, reliable data pipelines and data infrastructure using Spark and related technologies.
- Build tooling, systems, frameworks, and developer environments that improve research and engineering productivity.
- Collaborate directly with researchers and cross-functional partners to accelerate experiments, improve infrastructure efficiency, and ship projects end to end.
Requirements
- Bachelor’s degree or equivalent experience in computer science, engineering, or a similar field.
- Proficiency in at least one backend language, particularly Python or Rust.
- Experience operating large-scale clusters and container orchestration systems such as Kubernetes or Slurm.
- Ability to work across the stack and own projects end to end in a highly collaborative environment.
- Preferred: strong debugging skills across application, operating system, and network layers.
- Preferred: proficiency with Python or Rust, containers, and modern CI; experience with Kubernetes controllers or operators or performance profiling; and familiarity with GPU/ML workflows or large-scale data and evaluation pipelines.
Benefits
- Annual base salary of $300,000-$400,000 USD.
- Health, dental, and vision benefits.
- Unlimited PTO and paid parental leave.
- Relocation support as needed.
- Visa sponsorship is offered, with commitment to work through the visa process for qualified candidates, though success is not guaranteed for every candidate or role.
- Based in San Francisco, California.
Tech Stack
Categories
About Thinking Machines Lab
Thinking Machines Lab develops AI and generative AI software and conducts applied research to help organizations make data-driven decisions. The company builds products and data science solutions for enterprise use cases, pairing foundational models with practical tooling and services across industries. It is privately held and headquartered in San Francisco.