Client Roles
ABOUT THE ROLE
Join a research team at an applied AI research and training data company, focused on understanding how datasets affect model behavior. You will design controlled post-training experiments and turn their results into evidence that informs data development and model improvement.
WHAT YOU'LL DO
- Run controlled supervised fine-tuning and reinforcement learning experiments to measure how datasets affect model performance.
- Build shared evaluation infrastructure and benchmarks that support reproducible findings across models, capabilities, and domains.
- Help develop public evaluations and new data types that advance model capabilities.
- Publish external-facing research, blog posts, and technical reports.
- Use experimental results to guide improvements to data quality in collaboration with internal teams.
- Work with partner research labs to communicate clear findings about data and model performance.
WHAT WE'RE LOOKING FOR
- 0 to 4 years of experience building or delivering work in LLM training, post-training, or model evaluation, including experience at a frontier AI lab.
- Familiarity with LLM training and evaluation methods, including SFT and RL-based post-training.
- Experience independently designing, implementing, and analyzing controlled experiments, and drawing actionable insights from imperfect results.
- Software engineering ability to build or modify experimental infrastructure, such as evaluation harnesses, training pipelines, or benchmarks.
- Ability to work across domains such as finance, software engineering, and polic