Research Engineer, Domain Scaling

Anthropic's mission is to create reliable, interpretable, and steerable AI systems.

The Domain Scaling team aims to make Claude world-class at real-world knowledge work in domains like finance, healthcare, and legal.

Responsibilities

• Own the data strategy for knowledge work verticals end-to-end, from task sourcing through RL training
• Manage technical relationships with external data vendors, including evaluation of data quality and reward design
• Collaborate with domain experts to design data pipelines and evaluations
• Explore novel ways of creating RL environments for high-value tasks
• Develop and improve QA frameworks to catch reward hacking and ensure environment quality
• Run generalization experiments to measure how data strategy changes improve model capabilities
• Partner with other RL research teams and product teams to translate capability goals into training environments and evaluations

Requirements

• Experience with fine-tuning large language models for specific domains or real-world use cases
• Experience with reinforcement learning, reward design, or training data curation for LLMs
• Comfortable managing technical vendor relationships and iterating quickly on feedback
• Strong cross-functional collaboration skills
• Passionate about making AI more useful and accessible across different industries

Nice to Have

• Experience training production ML systems
• Experience designing evaluations or benchmarks for LLMs
• Domain expertise in a vertical where Anthropic would like to make models more useful
• Experience working with external vendors or technical partners

The annual compensation range for this role is $1-$2 USD.