Software Engineer, Supercomputing
Thinking Machines Lab2 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 clear retention and lineage.
- Partner with researchers to unblock 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.
- Strong collaboration and initiative in cross-functional environments.
- Preferred: strong systems background in Linux, networking, and infrastructure-as-code.
- Preferred: familiarity with CUDA, NCCL, and performance profiling for distributed training and inference.
- Preferred: experience supporting large-scale model training or inference environments.
- Preferred: understanding of deep learning frameworks such as PyTorch, TensorFlow, or JAX and their underlying system architectures.
Benefits
- Based in San Francisco, California.
- Annual base salary range of $350,000-$475,000 USD.
- Visa sponsorship is available.
- Generous health, dental, and vision benefits.
- Unlimited paid time off.
- Paid parental leave.
- Relocation support as needed.
- Evergreen role with applications continuously reviewed; candidates are asked not to reapply more than once every six months.
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.