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 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 willBuild 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
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
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
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.
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
Intro call with HR (30 min)
Take-home exercise
Final conversation with our CEO (45 min)
Please submit your application in English.
