Software Engineer, Supercomputing
Thinking Machines Lab3 months ago
Base Salary
$350k - $475k/yr
Responsibilities
- Operate and automate large GPU clusters, including provisioning, imaging, and capacity planning.
- Write software that abstracts cluster management and provides a unified interface for training and inference.
- Extend Kubernetes, Slurm, or similar orchestration systems for topology-aware placement, preemption, quotas, and fair-share multi-tenancy.
- Monitor and improve speed, reliability, and error-recovery metrics.
- Build reliable storage and artifact paths for datasets, checkpoints, and logs with retention and lineage.
- Partner with researchers on large-scale runs and advise on parallelism and performance trade-offs.
Requirements
- Bachelor’s degree or equivalent experience in computer science, engineering, or a similar field.
- Proficiency in at least one backend language, specifically 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.
- Preferred qualifications include a strong systems background in Linux, networking, and infrastructure-as-code; familiarity with CUDA/NCCL and distributed-training performance profiling; experience supporting large-scale model training or inference environments; and familiarity with PyTorch, TensorFlow, or JAX.
Benefits
- Annual salary range of $350,000 - $475,000 USD.
- Based in San Francisco, California.
- Visa sponsorship is available, with the company committed to working through the visa process for suitable candidates, though success is not guaranteed for every candidate or role.
- Generous health, dental, and vision benefits.
- Unlimited PTO and paid parental leave.
- Relocation support as needed.
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.