Research Engineer, Infrastructure, Training Systems

Highlights

• Design distributed training infrastructure scaling across thousands of GPUs.
• Keep frontier training runs efficient and reliable through days-long jobs.
• Diagnose bottlenecks across compute, memory, networking and storage.

What they offer

• Generous health, dental and vision benefits
• Unlimited PTO
• Paid parental leave
• Relocation support as needed

Ideal candidate

Systems engineer who loves deep debugging across the training stack and turning insights into reliable, high-throughput infrastructure. Collaborative and curious, you partner closely with researchers to make frontier training faster.

Requirements

• Strong engineering skills writing performant, maintainable code and debugging complex systems
• Hands-on experience building, optimizing or operating distributed model-training infrastructure
• Depth in distributed training frameworks, parallelism, GPU communication, low-precision training, runtime systems or orchestration
• Understanding of deep learning frameworks such as PyTorch or JAX and the systems beneath them
• Ability to investigate problems across subsystem boundaries and carry solutions through implementation and validation
• Collaborative approach with clear communication about evidence, uncertainty and tradeoffs
• Bachelor's degree in relevant technical field or equivalent practical experience