Member of Technical Staff, AI Training Infrastructure

Highlights

• Build scalable infrastructure powering large-scale LLM and multimodal training.
• Optimize training performance across GPUs, nodes, and data centers.
• Architect data storage and automation for large-scale model training.

What they offer

• Equity

Ideal candidate

A builder obsessed with large-scale training efficiency who thrives collaborating with researchers to solve hard distributed systems challenges and ship reliable, high-performance infrastructure.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience
• 3+ years of experience with distributed systems and ML infrastructure
• Experience with PyTorch
• Proficiency in cloud platforms (AWS, GCP, Azure)
• Experience with containerization, orchestration (Kubernetes, Docker)
• Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)