Senior Applied ML Engineer (Agentic Search)

About the role

Nebius is seeking a Senior Applied ML Engineer to join a team building an agent-native search platform for AI systems. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale to help AI systems access reliable information in real time. This is a high-impact role working on a production system that operates 24/7.

Responsibilities

• Design, train, and deploy ML models for retrieval, reranking, and search relevance in production
• Build and optimise embedding-based indexing and large-scale retrieval systems
• Develop models supporting crawling, data selection, and content understanding
• Define and improve quality metrics for agent-native search and build evaluation pipelines
• Work on systems operating at very large scale, including high-throughput query workloads
• Collaborate closely with engineering teams to integrate ML models into production services
• Analyse performance trade-offs across latency, quality, and cost
• Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems
• Contribute to product and architectural decisions in a fast-moving environment

Required skills

• Python
• Go
• C++
• Machine Learning
• Deep Learning
• Retrieval
• Ranking
• Recommendation
• Large-scale data systems
• Production deployment

Nice to have

• Search systems
• Information retrieval
• Embeddings
• Transformers
• NLP
• LLM-powered systems
• Agent-based systems

Benefits

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture

About the Company

Nebius is a full-stack AI cloud platform supporting developers and enterprises from data and model training through to production deployment. Listed on Nasdaq, the company has a global footprint with R&D hubs across Europe, the UK, North America and Israel.