Week 2025-W40

Anthropic· 4 roles

• Data Operations Manager - Computer Use & Tool Use Data · Engineering 9
  This role focuses on building and scaling data operations for AI models, specifically for computer use capabilities and tool use safety. The manager will partner with research teams to design and execute data strategies, manage vendors, and own the data pipeline from requirements to production. The goal is to ensure AI models can use tools safely and operate computers autonomously, impacting agentic workflows. The role requires technical depth in ML workflows and RL environments, strategic thinking, and operational excellence.
• Research Operations & Strategy Lead - Coding & Cybersecurity Data Data · Research 9
  This role focuses on building and scaling data operations for AI models, specifically for coding and cybersecurity capabilities. The lead will partner with research teams to design and execute data strategies, manage vendors, and oversee the data pipeline from requirements to production. While not hands-on engineering, technical depth in understanding training data quality is required, with a focus on strategy and execution.
• Data Operations Manager Data · Engineering 7
  This role focuses on building and scaling data operations for AI research teams, managing the entire data pipeline from requirements to production. It involves partnering with researchers, managing vendors, and ensuring high-quality training data for frontier AI capabilities like RLHF, safety, tool use, and agentic workflows. The role requires operational excellence, technical depth in understanding training data, and strong project management skills.
• Software Engineer, Biology & Life Sciences Ship · Engineering 7
  Software Engineer to join the Life Science team, focusing on building robust, scalable AI systems to accelerate progress in life sciences. The role involves prototyping new products, developing critical infrastructure, and implementing efficient solutions for complex scientific problems, working at the intersection of AI and biology. Collaboration with researchers and domain experts is key, with a focus on translating biological requirements into technical implementations and ensuring Claude is capable of enabling complex workflows.