Senior ML Engineer (Agentic Search)

About the role

<div class="content-intro"><p><strong>About Nebius:</strong></p> <p>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.</p> <p>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.</p> <p>Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&amp;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&amp;D.</p></div><p>We are seeking a Senior ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI.</p> <p>You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time.</p> <p>This is a high-impact role working on a production system used 24x7, tackling challenges comparable to large-scale web search.</p> <p><strong>Your responsibilities:</strong></p> <ul> <li>Design, train, and deploy ML models for retrieval, reranking, and search relevance in production</li> <li>Build and optimise embedding-based indexing and large-scale retrieval systems</li> <li>Develop models supporting crawling, data selection, and content understanding</li> <li>Define and improve quality metrics for agent-native search and build evaluation pipelines</li> <li>Work on systems operating at very large scale, including high-throughput query workloads</li> <li>Collaborate closely with engineering teams to integrate ML models into production services</li> <li>Analyse performance trade-offs across latency, quality, and cost</li> <li>Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems</li> <li>Contribute to product and architectural decisions in a fast-moving environment</li> </ul> <p><strong>Must-haves:</strong></p> <ul> <li>5+ years of experience in software engineering or applied machine learning</li> <li>Strong programming skills in Python, Go, or C++</li> <li>Proven experience deploying ML models in production systems</li> <li>Hands-on experience with retrieval, ranking, recommendation, or similar ML problems</li> <li>Strong understanding of machine learning and modern deep learning techniques</li> <li>Experience working with large-scale data systems and high-throughput environments</li> <li>Ability to design evaluation frameworks and define meaningful model metrics</li> <li>Product-oriented mindset with a focus on impact and iteration</li> <li>Strong problem-solving skills and ability to work in a distributed team</li> </ul> <p><strong>Nice-to-haves:</strong></p> <ul> <li>Experience with search systems or large-scale information retrieval</li> <li>Familiarity with embeddings, transformers, and modern NLP systems</li> <li>Experience working on LLM-powered or agent-based systems</li> <li>Contributions to open-source projects, technical publications, or conference talks</li> <li>Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability</li> </ul><div class="content-conclusion"><p><strong>Benefits &amp; Perks:</strong></p> <ul> <li>Competitive compensation</li> <li>Career growth and learning opportunities</li> <li>Flexibility and ownership</li> <li>Collaborative and innovative culture</li> <li>Opportunity to work on impactful AI projects</li> <li>International environment and talented teams</li> </ul> <p><strong>What's it like to work at Nebius:</strong></p> <p>Fast moving&nbsp;- Bold thinking&nbsp;- Constant growth&nbsp;- Meaningful impact&nbsp;- Trust and real ownership&nbsp;- Oppo

Skills