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 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 recently raised our Series A funding round, taking our total funding to $70M. Our investors include 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 ML/AI Research, Multimodal ML Engineer, Research Scientist (AI Behaviours, Evals, Agentic Systems), and ML Infra roles

Develop a deep understanding of White Circle’s research agenda, technical challenges, and the profiles required to solve them

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

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 behaviour, 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+)

A big plus

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

Compensation & benefits

Competitive compensation package, including equity

Flexible time off

Health insurance

Mental health support, including coverage for therapy when you need it

401(k) retirement plan

Learning and development support for courses, conferences, and opportunities to grow your skills

All the hardware, subscriptions, tools, and services you need

Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella

Process

Introductory call with Head of People (25 min)

Take-home assignment

Final conversation with CEO & Head of Applied Research (45 min)

Please submit your application in English.