ML Research Engineer

Npv; Paris; Hybrid; EUR 65,000 - 90,000; Full time

Benefits offered by this job

Relocation support

Hybrid work (Paris/London)

Healthy & mental health support

Job summary

White Circle is seeking ML Engineers to build safety, reliability, and optimization layers for AI systems. You will design scalable NLP pipelines, embeddings, and detection workflows, collaborating with engineering and research to meet latency and privacy constraints.

The role requires production-grade pipeline engineering, experience with large-scale data, and hands-on work with embeddings, topic modeling, and semantic search.

Qualifications

• 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, drift monitoring.

Responsibilities

• 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).
• Experience at scale: distributed processing, large-scale storage and querying, performance-cost tradeoffs.

Skills

Python

SQL

NLP

embeddings

Tools

HuggingFace

GitHub

Job description

Relocation support is mentioned in the posting.

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.

• 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).
• 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.
• 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.
• 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.