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Anthropic is seeking an Engineering Manager to lead the Scheduler team responsible for scheduling and fleet efficiency across Anthropic's compute resources. You will guide a team building infrastructure used by researchers and engineers to launch and manage their jobs, while collaborating with capacity planning, research, and product teams to optimize workloads and system performance.
The role emphasizes leadership, platform reliability, and developing an inclusive, high-performing team in a
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
Anthropic's compute fleet is one of the largest and most varied in the world, and everything we do from training frontier models to serving Claude depends on getting the right work onto the right hardware at the right time. Our Scheduler team owns that problem. We build the scheduling layer for Anthropic's Kubernetes fleet, the tools researchers and engineers use to launch and manage their jobs, and the systems that make sure the fleet is used as efficiently as possible. When a researcher starts a run, the scheduler decides where it lands and how quickly; when demand outstrips supply, it decides who waits. This team provides the paved path that lets everyone at Anthropic get compute when they need it without becoming an expert in the infrastructure underneath.
We're looking for an engineering manager to lead this team. The scheduler is on the critical path for nearly all of Anthropic's compute, and the mandate is expanding quickly: making scheduling work seamlessly across a growing, heterogeneous fleet; raising utilization while keeping jobs starting fast; making the system's decisions predictable and explainable to the people who depend on it; and making the job-launch experience something researchers rarely have to think about. You'll lead a team building infrastructure that the entire research and product organization depends on, and you'll partner closely with capacity planning, research, inference, and product teams to make efficient use of the fleet.