Software Engineer, ML Infrastructure, Reality Labs Research

Set technical direction for and lead the design, build, and operation of large-scale, multi-tenant GPU/ML training, inference, rendering, and general compute infrastructure on Kubernetes Drive cross-team and org-level initiatives that improve cluster reliability, scheduling efficiency, utilization, and scale, including datacenter and hardware migrations and expansions Our reliability for the cluster end to end: participate in and improve oncall and incident response, and build the automation and observability that reduces operational costs Define and drive best practices in system design, testing, code health, and operational excellence across the team Partner with research and infrastructure teams to translate ML workload requirements into platform capabilities, and influence architecture and technical decisions beyond your immediate team Mentor engineers, review designs, and improve the overall technical quality of the team's work through code reviews, design guidance, and knowledge sharing