Research Engineer, Production Model Post-Training

<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's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.</p> <p>You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.</p> <p><em>Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends.</em></p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Implement and optimize post-training techniques at scale on frontier models</li> <li>Conduct research to develop and optimize post-training recipes that directly improve production model quality</li> <li>Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation</li> <li>Develop tools to measure and improve model performance across various dimensions</li> <li>Collaborate with research teams to translate emerging techniques into production-ready implementations</li> <li>Debug complex issues in training pipelines and model behavior</li> <li>Help establish best practices for reliable, reproducible model post-training</li> </ul> <h2><strong>You may be a good fit if you:</strong></h2> <ul>