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Head of Data Labeling

whitecircle · Remote, France

Data Science / AI / Machine LearningManager LevelRemoteQuick applyfull-time21 days ago

About The Role

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 100M+ 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 at a multi-million dollar run rate already having signed customers like Lovable and multiple neobanks. You’ll be joining at the most exciting time - early enough that the equity can be life changing but at a point where demand has been proven.

IN THIS ROLE, YOU WILL

  • Build from scratch and lead the Data Labeling team (hiring, coaching, and performance management)
  • Define annotation guidelines, quality standards, and evaluation frameworks
  • Develop quality assurance processes, calibration sessions, and auditing systems
  • Partner with AI researchers and engineers to translate research objectives into labeling workflows
  • Prioritise labeling projects based on business and research needs
  • Monitor operational metrics including quality, consistency, throughput, and cost
  • Improve annotation tooling, automation, and workflow efficiency
  • Lead complex AI evaluation projects, including safety, preference ranking, RLHF, policy evaluation, and benchmark creation
  • Analyse disagreement patterns and edge cases to improve guidelines and model performance
  • Manage vendor relationships and ensure consistent quality across distributed teams
  • Build reporting dashboards and communicate operational insights to leadership
  • Foster a culture of continuous improvement, accountability, and operational excellence

WE'RE LOOKING FOR SOMEONE WHO

  • Has experience leading data annotation or AI evaluation teams
  • Has strong operational and people management skills
  • Understands AI model evaluation, LLM behavior, and modern annotation workflows
  • Can design scalable processes without sacrificing quality
  • Communicates clearly across technical and non-technical teams
  • Thrives in fast-moving startup environments

YOU MIGHT BE A GREAT FIT IF YOU

  • Have managed annotation programs for LLMs, generative AI, or machine learning
  • Have experience with RLHF, preference data collection, safety evaluations, or benchmark creation
  • Have worked in Trust & Safety, AI Safety, Content Moderation, or ML Ops
  • Have managed distributed or global annotation teams
  • Have experience with vendor management and outsourcing operations

BONUS POINTS

  • Familiarity with prompt engineering and AI safety policies
  • SQL, Python, or data analysis experience
  • Experience building internal annotation platforms or workflow automation
  • Background in linguistics, cognitive science, machine learning, or data operations
  • Important note
  • This role involves overseeing projects that may include offensive, harmful, violent, sexual, or otherwise disturbing content.
  • You'll be responsible for ensuring reviewers have the tools, guidance, and support necessary to perform this work safely and consistently.

WHY WHITE CIRCLE

  • Competitive salary + equity
  • Work from Paris (hybrid) with a relocation package available, or work from London (note: we are currently unable to provide relocation support and medical insurance for London-based roles)
  • Paid time off in line with your local regulations
  • All the hardware, tools, and services you need
  • Covered subscriptions for AI agents and IDEs
  • Team off-sites twice a year: we’ve recently been to the Alps and Saint-Tropez

HOW WE HIRE

  1. Intro call with HR (30 min)
  2. Take-home exercise
  3. Final conversation with our CEO (45 min)

Please submit your application in English.

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