{"id":720960,"url":"https://alion.io/job/whitecircle-recruiter-research","title":"Recruiter (Research)","company":{"id":720703,"name":"Whitecircle","domain":"whitecircle.com","url":"https://alion.io/company/whitecircle-2","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":93,"open_postings":13,"ghost_share":0,"stale_share":0.077,"repost_share":0,"time_to_fill_p50_days":107,"computed_at":"2026-11-02T06:13:15Z"}},"role":"HR","role_family":"HR","seniority":"junior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":56000,"max_usd":108000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":230},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Anthropic","optional":true},{"name":"Datadog","optional":true},{"name":"Hugging Face","optional":true},{"name":"Mistral","optional":true},{"name":"OpenAI","optional":true}],"status":"live","first_seen_at":"2026-08-10T21:13:01Z","employer_posted_date":"2026-08-10","last_verified_at":"2026-11-03T02:05:09Z","board_verified":true,"closed_at":null,"days_open":84,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":83},"description":"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.\nAbout us\nWhite 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.\nWe’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\n\nWe process over one hundred million API calls every month\n\nWe fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model\n\nWe’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.\nYou will\nOwn full-cycle recruitment for ML/AI Research, Multimodal ML Engineer, Research Scientist (AI Behaviours, Evals, Agentic Systems), and ML Infra roles\n\nDevelop a deep understanding of White Circle’s research agenda, technical challenges, and the profiles required to solve them\n\nSource talent from AI labs, research organisations, technical startups, universities, open-source communities, and relevant scientific networks\n\nUnderstand the differences between Research Scientists, Research Engineers, Applied ML Engineers, and ML infra Engineers & assess candidates accordingly\n\nEvaluate candidates’ actual contributions\n\nEngage researchers and engineers who are not actively looking for a new role and communicate why White Circle’s problems are technically meaningful\n\nDesign structured hiring processes that assess research depth, engineering ability, originality, and real-world impact\n\nDeliver an exceptional candidate experience, including for candidates navigating multiple highly competitive opportunities\n\nTrack recruiting performance and continuously improve sourcing strategies, processes, tools, and workflows\n\nSupport hiring outside your primary stream when business priorities require it\n\nYou’ll fit right in if you\nHave 2+ years of full-cycle recruiting experience, including significant experience hiring Research and ML talent\n\nHave personally hired for several roles comparable to Research Scientist, Research Engineer, ML Research Engineer, Applied Scientist, Multimodal ML Engineer, or ML Infrastructure Engineer\n\nUnderstand what these roles do and how their responsibilities, technical depth, and candidate pools differ\n\nCan confidently discuss LLM training and fine-tuning, inference, evaluations, data pipelines, model behaviour, multimodal learning, agent systems, and ML infra\n\nCan interpret technical profiles beyond keywords, job titles, or company names\n\nKnow how to assess the significance of a candidate’s publications, open-source work, models, datasets, experiments, and production systems\n\nUnderstand where exceptional AI research talent can be found and how to reach candidates who are not visible through conventional sourcing channels\n\nParticipate in or closely follow AI research and engineering communities\n\nCan build credibility with highly technical candidates and communicate nuanced research problems accurately\n\nHave experience recruiting across the US and European markets\n\nCan act as a trusted talent advisor to technical hiring managers and research leadership\n\nAre comfortable operating with ambiguity and continuously refining profiles as research priorities evolve\n\nAre willing and able to recruit beyond Research roles when needed\n\nSpeak and write fluent English (C1+)\n\nA big plus\nExperience recruiting for a frontier AI lab, AI safety org, research-focused startup, or leading AI company\n\nA strong existing network among AI researchers, research engineers, and ML infra specialists\n\nExperience sourcing through publications, conference programs, citations, GitHub, open-source projects, research communities, and academic labs\n\nA technical or research background in computer science, machine learning, mathematics, or a related field\n\nExperience recruiting for an early-stage startup where the research direction and hiring requirements evolve quickly\n\nCompensation & benefits\nCompetitive compensation package, including equity\n\nFlexible time off\n\nHealth insurance\n\nMental health support, including coverage for therapy when you need it\n\n401(k) retirement plan\n\nLearning and development support for courses, conferences, and opportunities to grow your skills\n\nAll the hardware, subscriptions, tools, and services you need\n\nTeam off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella\n\nProcess\nIntroductory call with Head of People (25 min)\n\nTake-home assignment\n\nFinal conversation with CEO & Head of Applied Research (45 min)\n\nPlease submit your application in English.","description_format":"text","description_chars":5155,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":["Equity","Flexible time off","Health insurance","Retirement plans"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI Safety & Alignment"],"lifecycle":[{"event":"open","at":"2026-09-11T07:11:36Z"}],"visa":[],"liveness":{"score":48,"band":"ok","label":"Likely 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