whitecircle - Research Scientist (AI Behaviours)

• Own research projects end to end — from an unclear concern ("how do we even define sloppy research outputs?") to a falsifiable experiment, clean baselines, and a result you can defend. • Develop automated audit agents that discover and characterise suspect model behaviour at scale. • Study how misalignment and bias actually show up when real users interact with agents, and turn what you find into evals our products can ship. • Pressure-test frontier agents in realistic, high-stakes scenarios to find where they break before our customers do. • Run white-box and block-box investigations to understand how AI models fail. • Publish what you learn as public blog posts and conference papers, and feed the rest back into our internal guardrails. • You’ll fit right in if you: • A track record of empirical research in agent behaviour, model evaluation, alignment, or a closely adjacent area. • Strong ML engineering. You can independently build a research MVP involving fine-tuning, agent inference, and evals, without waiting on a platform team. • Evidenced skills in experimental design under real conditions: isolating agent failure modes, calibrating judges and baselines, and distinguishing genuine signal from artifact. • You can take a vague behavioural question and define the experiment that answers it, when there's no playbook — then run it fast and iterate. • An AI power-user — fluent with frontier models and coding agents in your daily work. • Published research at A* venues (NeurIPS / ICML / ICLR / ACL and similar). • Interpretability depth — familiarity with modern interp tooling and concepts (NLAs, SAEs, persona vectors, etc.) and the ability to run whitebox investigations on our internal and open-source models. • An MSc or PhD in machine learning, computer science, cognitive science, computational neuroscience, physics, or a related quantitative field. • AI safety fellowship (MATS, ASTRA, Anthropic Fellows, etc.), or a comparable self-directed research record.