Recruiter (Research)

Summary

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. They are seeking an AI Research Recruiter to manage full-cycle hiring for roles in AI research and machine learning, partnering with leadership to define candidate profiles and source exceptional talent.

Responsibilities

• 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

Skills

• 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 to recruit beyond research roles when needed
• Speak and write fluent English (C1+)
• Experience recruiting for a frontier AI lab, AI safety org, research-focused startup, or leading AI company
• A strong existing network among AI researchers, research engineers, and ML infra specialists
• Experience sourcing through publications, conference programs, citations, GitHub, open-source projects, research communities, and academic labs
• A technical or research background in computer science, machine learning, mathematics, or a related field
• Experience recruiting for an early-stage startup where the research direction and hiring requirements evolve quickly

Qualifications

Must Haves

• 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 to recruit beyond research roles when needed
• Speak and write fluent English (C1+)

Nice to Haves

• Experience recruiting for a frontier AI lab, AI safety org, research-focused startup, or leading AI company
• A strong existing network among AI researchers, research engineers, and ML infra specialists
• Experience sourcing through publications, conference programs, citations, GitHub, open-source projects, research communities, and academic labs
• A technical or research background in computer science, machine learning, mathematics, or a related field
• Experience recruiting for an early-stage startup where the research direction and hiring requirements evolve quickly

Benefits

• Meaningful equity package
• Paid time off in line with your local regulations, no matter where you work from
• All the hardware, tools, and services you need
• Covered subscriptions for AI agents
• Team off-sites twice a year: we’ve recently been to the Alps and to Saint-Tropez
• REMOTE / work from home arrangement (workplace_type: Remote)