ML Research Engineer
We're looking for ML Engineers to join White Circle , an AI Safety company building the policy enforcement and optimization layer for AI systems. Backed by $11M from senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, and DeepMind, White Circle processes 100M+ API calls monthly and runs its own LLMs in production. You will Turn petabytes of unstructured text into a structured, explorable view: topics, clusters, segments, trends, anomalies. Build scalable representation pipelines: sampling, preprocessing, embeddings at scale, indexing, and retrieval. Use LLMs for labeling, weak supervision, data enrichment, and automated diagnostics, with cost/quality controls. Translate findings into product and operational decisions, and ship self-serve datasets, data models, and dashboards. Work with engineering and research to align pipelines with production constraints (latency, cost, privacy).
Requirements Strong Python and SQL, with production-grade pipeline engineering (not just notebooks). Applied NLP/ML on real-world text: embeddings, clustering, topic modeling, semantic search, classification. Experience at scale: distributed processing, large-scale storage and querying, performance-cost tradeoffs. Evaluation of fuzzy problems: offline/online metrics, human-in-the-loop labeling, inter-annotator agreement, drift monitoring. Prior work with safety/moderation datasets, policy/rule systems, or high-volume logging/observability. Relocation to Paris or London (hybrid) required. Bonus Public builder footprint: open-source models, datasets, or frameworks on HuggingFace/GitHub, papers, or technical posts. Experience at a frontier or near-frontier lab, or leading open-source model releases. RL for LLMs beyond standard RLHF: online RL, GRPO-style methods. Moderation, safety, or classification models at scale; multilingual model training.
We offer Competitive salary + equity.
Hybrid work from central London or Paris office, relocation support for Paris after probation.
- Premium private health insurance
- mental health support
- flexible time off
- Lunch and dinner covered in the office
- L&D budget
- all hardware and tools you need
- Team off-sites twice a year