ML Research Engineer

We're looking for ML Engineers to join White Circle , an AI Safety company building the safety, reliability, and optimization layer for AI systems through natural-language policies it automatically tests, enforces, and improves at scale. Backed by $70M (Series A) from top funds and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, and others, White Circle processes 100M+ API calls monthly and fine-tunes and trains its own LLMs to run faster and cheaper than open or proprietary models.
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.

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Source: Arbeitnow (https://www.arbeitnow.fr/jobs/companies/npv/ml-research-engineer-paris-357030)