Research Engineer, Pretraining Scaling

<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><strong>About the Role:</strong></h2> <p>Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.</p> <p>This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.</p> <h2><strong>Responsibilities:&nbsp;</strong></h2> <ul> <li>Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability</li> <li>Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure</li> <li>Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance</li> <li>Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams</li> <li>Build and maintain production logging, monitoring dashboards, and evaluation infrastructure</li> <li>Add new capabilities to the training codeb