Research Engineer, Domain Scaling

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 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

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
• Value in reading through datasets to understand them and spot issues
• Strong cross-functional collaboration skills
• Passionate about making AI more useful and accessible across different industries
• Excited about a role that includes a combination of applied research and hands-on data work

Nice-to-Haves

• Experience training production ML systems
• Experience designing evals or benchmarks for LLMs
• Domain expertise in a vertical where models would be more useful
• Experience working with external vendors or technical partners

Education

• Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role

Compensation

• Annual Salary: $1—$2 USD