Staff Software Engineer, AI Runtime

Highlights

• Build a serverless GPU training platform spanning thousands of accelerators.
• Power custom training from fine-tuning to frontier-scale foundation models.
• Keep week-long multi-node jobs running with resilient, high-throughput systems.

What they offer

• Annual performance bonus
• Equity
• Comprehensive benefits

Ideal candidate

A veteran distributed-systems builder passionate about large-scale AI training who thrives on hard performance and reliability challenges and leads through vision, mentorship, and end-to-end ownership.

Requirements

• 10+ years building and operating large-scale distributed systems with depth in GPU training infrastructure, HPC, or ML systems
• Hands-on experience with distributed training frameworks and data, tensor, pipeline, and sequence parallelism for large models
• Strong understanding of training resilience patterns including checkpointing, failure detection, and automatic recovery for multi-node jobs
• Solid grasp of GPU performance fundamentals including accelerator architecture