Research Engineer, Domain Scaling

The shape of it

In the posting’s own words

The Domain Scaling team has the goal to make Claude world-class at real-world knowledge work in domains like finance, healthcare, and legal. This is a unique role that combines executing directly on applied research and data sourcing (real-world and synthetic) to improve our models. You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.

What it asks for · 7

• Have experience with fine-tuning large language models for specific domains or real-world use cases
• Have experience with reinforcement learning, reward design, or training data curation for LLMs
• Are comfortable managing technical vendor relationships and iterating quickly on feedback
• Find value in reading through datasets to understand them and spot issues
• Have strong cross-functional collaboration skills
• Are passionate about making AI more useful and accessible across different industries
• Are excited about a role that includes a combination of applied research and hands-on data work

Also a plus

• Have experience training production ML systems
• Have experience designing evals or benchmarks for LLMs
• Have domain expertise in a vertical where we would like to make our models more useful
• Have experience working with external vendors or technical partners

What the job covers

• 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 envs for high value tasks
• Develop and improve QA frameworks to catch reward hacking and ensure env 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 envs and evals

Tools and skills named

Words the posting leans on

• data15×
• experience10×
• domain8×
• models8×
• training8×
• reward7×
• vendors7×
• envs6×
• technical6×
• improve5×
• tasks5×
• data strategy4×
• evals4×
• evaluation4×
• external4×
• llms4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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