nebius · London, United Kingdom
Skills: Python
About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. In a rapidly evolving world, trust in AI depends on agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We’re looking for an experienced Data Analyst who has built evaluation systems for complex technology products and is excited to take end-to-end ownership of quality in search built for AI agents. This role combines hands-on engineering, analytical judgment, and mathematical rigor, with the scope and influence to shape both technical decisions and product direction. We move at a startup pace, with plenty of open questions and difficult problems to solve. In this position, you will: • Own the quality measurement and improvement cycle end-to-end: identify user needs, define success, build evaluations, diagnose failures, and work with engineers and product managers to improve outcomes.. • Design, build, and evolve evaluation systems, including datasets, benchmarks, metrics, and automated pipelines that support development and launch decisions.. • Evaluate response quality across multiple dimensions, including relevance, completeness, freshness, factual accuracy, and usefulness to downstream agents.. • Investigate quality regressions and metric anomalies, uncover root cause…
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