Staff+ Software Engineer, ML Inference Path

<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><h3><strong>About the role:</strong></h3> <p>The Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML based safety systems. We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch. And we build for scale: serving thousands of ML classifiers, for all requests on the token generation path, and for every platform Claude runs on -- 1P, Bedrock, Vertex, and beyond.</p> <p>We’re growing the team and looking for engineers who have deep expertise in productionizing ML systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale. And your tooling and infrastructure will be used for every model launch, which are becoming more complex, and more frequent.</p> <h3><strong>Responsibilities:</strong></h3> <ul> <li>Design and build scalable ML infrastructure to support real-time safety deployments across our classifier and model ecosystem</li> <li>Build monitoring and observability tools to track classifier performance, data quality, and system health for safety-critical applications</li> <li>Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems</li> <li>Optimize inference latency and throu