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-annotato