Research Engineer, Domain Scaling

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society.

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 its models more useful
• Experience working with external vendors or technical partners

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