Pre-training Distributed Systems Tech Lead / Manager

<div class="content-intro"><h2><strong>About Anthropic</strong></h2> <p>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.</p></div><h2>About the Role</h2> <p>Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We're looking for an experienced tech lead to join our Evals Infrastructure team, building the systems that let us measure what our models can actually do. Evaluation is how we know whether a model is safe to ship — you'd own the infrastructure that makes those measurements fast, reliable, and trustworthy at scale. In this role you'll work at the intersection of inference, research and infrastructure engineering: managing the large scale distributed systems that orchestrate evals for our frontier models, building and scaling the harnesses researchers use to design and run evals, making results reproducible and interpretable, and ensuring eval signal is available where decisions get made. Your work directly shapes what we build and what we don't.</p> <div><strong>Responsibilities</strong></div> <ul> <li>Lead the team building the distributed systems that schedule, orchestrate, and execute evals for our frontier model training</li> <li>Own eval throughput and cost: compute allocation across suites, queueing against constrained accelerator pools, caching and reuse of eval work</li> <li>Build and scale the harnesses researchers use to define, run, and iterate on evals</li> <li>Make eval results trustworthy — determinism, reproducibility, and honest uncertainty quantification on reported metrics</li> <li>Ensure eval signal reaches the dashb