Member of Technical Staff, Research Engineering · Anthropic

You'll work directly on training and deploying frontier large language models — pre-training, fine-tuning, RLHF, evals, interpretability, or alignment research, depending on where your strengths fit. What the role actually involves: writing production training code at scale (PyTorch, large distributed clusters), running rigorous experiments with clear hypotheses, and communicating results to research leadership. Less about novel academic ideas; more about disciplined execution against an existing research agenda. Honest fit signals: — You've shipped ML systems that ran in production, not just notebook prototypes. Multi-node training experience matters here. — You're comfortable with the safety-first ethos: this is the team that wrote Constitutional AI and runs the Frontier Red Team. If you're primarily motivated by capability scaling, the culture friction will be real. — Strong written communication. Anthropic's engineering culture is doc-driven; you'll write design docs, postmortems, and research notes more than you'd expect. What's not a fit: pure researchers without engineering taste, engineers without ML systems experience, or anyone who wants a faster product iteration loop than a safety lab will give you.