Distributed Systems Engineer for AI Model Training and Inference

Distributed Systems Engineer - San Francisco, CA

A company building frontier-scale AI models that automate software engineering and AI research, combining ultra-long context, domain-specific RL, and massive compute infrastructure are looking for a Distributed Systems Engineer to join their team.

What Will I Be Doing:

• Design and build distributed data and coordination systems that enable ultra-long-context model training and inference
• Develop high-performance storage and caching systems to support large-scale GPU workloads
• Work deep in the internals of modern deep learning frameworks in highly distributed environments
• Build automation for fault detection, recovery and high availability across GPU clusters
• Troubleshoot complex, cross-stack issues spanning GPUs, networking, storage, operating systems and cloud infrastructure

What We’re Looking For:

• Deep expertise in distributed systems design and public cloud platforms
• Proven experience designing and operating highly available, high-throughput data systems
• Strong knowledge of distributed databases, batch or stream processing systems, and/or distributed file systems
• Exceptional problem-solving ability across the full systems stack
• A hands-on mindset with the curiosity and grit to learn fast in a frontier technical environment

What’s In It for Me:

• Salary of $225K–$550K dependent on experience + significant equity
• Great benefits inc. 401(k) with 6% company match, comprehensive health, unlimited PTO
• Visa sponsorship and SF relocation stipend available
• Well-funded ($465M+) with backing from top investors

Apply now for immediate consideration!