Thinking Machines Lab
Software Engineer, Supercomputing
$350K–$475K
San Francisco · On-site · Full-time · Posted Aug 4, 2026
- Education
- Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
- Visa sponsorship
- We sponsor visas.
About the job
Designs, builds, and operates GPU supercomputing infrastructure for large-scale model training and inference.
What you'll do
- Operate and automate GPU clusters, including provisioning, imaging, and capacity planning.
- Build cluster-management software and extend scheduling and orchestration for placement, preemption, quotas, and multi-tenancy.
- Improve reliability, performance, storage, and operational recovery while partnering with researchers on scale runs.
What they ask for
- Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
- Proficiency in at least one backend language; the posting uses Python or Rust.
- Experience operating large-scale clusters and container orchestration systems such as Kubernetes or Slurm.
- Comfort operating across the stack and owning projects end-to-end.
Nice to have
- Strong systems background in Linux, networking, and infrastructure-as-code.
- Familiarity with CUDA/NCCL, distributed-training performance profiling, or deep learning frameworks such as PyTorch, TensorFlow, and JAX.
Pay
$350,000 - $475,000 USD (base salary)
Tools
Python, Rust, Kubernetes, Slurm, Linux, CUDA/NCCL, PyTorch, TensorFlow
AI focus
Supports large-scale model training and inference environments, including compute, scheduling, and performance.
Model-written summary · the original posting is authoritative