Recruiter (Research)

TL;DR: We’re looking for an AI Research Recruiter who knows where exceptional AI Researchers and engineers can be found. You’ll own full-cycle hiring across research, machine learning, data, evaluations, and ML infrastructure, helping us build one of the strongest teams in AI safety. ABOUT US White Circle https://whitecircle.ai is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale. - We’ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others - We process over one hundred million API calls every month - We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need. YOU WILL: - Own full-cycle recruitment for AI Research, ML, data, evaluations, and ML infra roles - Develop a deep understanding of White Circle’s research agenda, technical challenges, and the profiles required to solve them - Partner closely with research leadership and CEO to define highly specialised candidate profiles - Source talent from AI labs, research organisations, technical startups, universities, open-source communities, and relevant scientific networks - Understand the differences between Research Scientists, Research Engineers, Applied ML Engineers, and ML infra Engineers & assess candidates accordingly - Evaluate candidates’ actual contributions - Engage researchers and engineers who are not actively looking for a new role and communicate why White Circle’s problems are technically meaningful - Follow developments in AI safety, model behavior, evaluations, multimodal systems, agentic systems, data quality, post-training, and ML infrastructure - Design structured hiring processes that assess research depth, engineering ability, originality, and real-world impact - Deliver an exceptional candidate experience, including for candidates navigating multiple highly competitive opportunities - Track recruiting performance and continuously improve sourcing strategies, processes, tools, and workflows - Support hiring outside your primary stream when business priorities require it YOU’LL FIT RIGHT IN IF YOU: - Have 2+ years of full-cycle recruiting experience, including significant experience hiring Research and ML talent - Have personally hired for several roles comparable to Research Scientist, Research Engineer, ML Research Engineer, Applied Scientist, Multimodal ML Engineer, or ML Infrastructure Engineer - Understand what these roles do and how their responsibilities, technical depth, and candidate pools differ - Can confidently discuss LLM training and fine-tuning, inference, evaluations, data pipelines, model behavior, multimodal learning, agent systems, and ML infra - Can interpret technical profiles beyond keywords, job titles, or company names - Know how to assess the significance of a candidate’s publications, open-source work, models, datasets, experiments, and production systems - Understand where exceptional AI research talent can be found and how to reach candidates who are not visible through conventional sourcing channels - Participate in or closely follow AI research and engineering communities - Can build credibility with highly technical candidates and communicate nuanced research problems accurately - Have experience recruiting across the US and European markets - Can act as a trusted talent advisor to technical hiring managers and research leadership - Are comfortable operating with ambiguity and continuously refining profiles as research priorities evolve - Are willing and able t…