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