Anthropic Benefits Overview

Conduct machine learning research for AI systems capable of engineering and scientific discovery. Design reinforcement learning environments, rewards, training data, benchmarks, simulations, and evaluation frameworks for frontier models. Develop methods for long-horizon reasoning, multi-agent collaboration, and learning from real-world feedback. Scale successful research into production training runs, validate systems with domain experts and industry partners, and assess robustness, calibration, generalization, and real-world impact.

Own internal communications for Anthropic’s Product organization, advising executives, drafting leadership communications, translating technical work into clear narratives, and planning forums such as all-hands and AMAs. The role anticipates communications needs around launches, incidents, organizational change, and sensitive security matters; strengthens communication channels; and partners with internal communications colleagues to ensure consistent updates across the company.

Develops evaluation methods, tasks, simulations, training environments, benchmarks, and datasets to measure and improve Claude’s engineering and applied science capabilities. The role collaborates with researchers, engineers, manufacturers, laboratories, and industry partners to validate AI-generated designs against real-world data, advise on impactful workflows, and translate engineering expertise into machine learning objectives.