Software Engineer Supercomputing

You will design, build, and operate GPU supercomputing infrastructure for large-scale training and inference. You will automate cluster operations, develop cluster-management software, extend scheduling and orchestration, improve performance and reliability, manage storage paths, and advise researchers on parallelism and performance trade-offs.

Responsibilities

• Operate and automate large GPU clusters, including provisioning, imaging, and capacity planning.
• Write software that abstracts cluster management for training and inference.
• Extend scheduling and orchestration for topology-aware placement, preemption, quotas, and multi-tenancy.
• Monitor and improve speed, reliability, and error recovery.
• Build reliable storage and artifact paths for datasets, checkpoints, and logs.
• Partner with researchers to unblock 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 a backend programming language.
• Experience operating large-scale clusters and container orchestration systems.
• Ability to work across the stack and own projects end to end.
• Experience collaborating with cross-functional partners and subject-matter experts.
• Ability to take initiative across stacks and teams to ensure delivery.

Benefits

• Health, dental, and vision benefits.
• Unlimited PTO.
• Paid parental leave.
• Relocation support as needed.