AI Researcher

Role overview Research how to help AI models develop new capabilities and determine whether training approaches work. You’ll take research questions from experiment design through datasets, evaluations, and analysis, then turn findings into improved data or training strategies. Projects may involve agents, model evaluation, human or synthetic data, failure analysis, or post-training.

Responsibilities - Design and run experiments to study model behavior and test research ideas. - Build datasets, benchmarks, agent environments, rubrics, and evaluation methods for capabilities that are not yet well measured. - Analyze model failures and use findings to inform data and training approaches. - Use fine-tuning or post-training experiments when useful to test hypotheses and measure capability changes. - Work with research partners to turn broad model-development goals into concrete investigations. - Communicate results through evaluations, technical reports, benchmarks, or papers.

Requirements - Comfort writing code, analyzing data, and independently moving experiments forward. - Ability to design rigorous experiments and draw useful conclusions from model evaluations. - Research or engineering experience is useful, though no single background is required.

Benefits and work setup Global, remote-first work with periodic in-person gatherings every few months. The role offers ownership from research question to conclusion and collaboration on evaluation, data, and post-training challenges. Compensation includes a stock option plan.