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.
The Product
In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.
We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.
The Role
As a Senior Software Engineer on a search vertical, you'll help build systems that capture what is true about a domain. You'll work on extracting, connecting, retrieving, and reasoning over knowledge from the web and beyond, turning messy, real-world data into structured, trustworthy knowledge so AI agents can answer questions with precision and completeness.
You will optimize the retrieval and knowledge layer for a vertical: how a domain's content is indexed, linked into entities, ranked, and continuously refreshed, then measured and improved against rigorous IR metrics. This is an information-retrieval and systems role spanning indexing internals, hybrid retrieval, and entity resolution, with the goal of making each vertical the best place in the world to search its domain.
In this position, your responsibility will be to
Design, implement, and operate the retrieval system for a search vertical
Connect and tune the data pipeline, from ingestion to relevance tuning
Build knowledge-graph and entity-resolution layers: entity linking / NER, ontologies, and graph databases (Neo4j or similar)
Develop structured-extraction pipelines over messy, unstructured domain data
Reason about freshness and trust: model how confident we are in a fact and how stale it has become before we serve it
Define evaluation and quality metrics for relevance and drive measurable improvements
Collaborate with crawling, indexing, and ML teams to ensure retrieval and ranking requirements are met
Enable safe experimentation with retrieval, ranking, and extraction strategies
You may be a good fit if you:
6+ years of software engineering experience, some of it in search / information retrieval
Strong IR fundamentals: inverted indexes, BM25/TF-IDF, query understanding, ranking, and evaluation (nDCG/MRR/recall@k)
Experience with vector & hybrid retrieval: ANN, dense+sparse fusion, embeddings models
Experience building structured extraction over messy/unstructured domain data
Fluent in Python and comfortable with systems-level performance work
Strong candidates may also have experience with:
Knowledge graphs: entity resolution, entity linking / NER, graph DBs (Neo4j), ontologies / schema design
Owning relevance / ranking for a real product and improving it against IR metrics
Data quality, truth discovery, or systems that decide how much to trust a piece of information
Published work on IR, ranking, or knowledge graphs
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Skills Required
- 6+ years of software engineering experience, some in search / information retrieval
- Strong IR fundamentals: inverted indexes, BM25/TF-IDF, query understanding, ranking, evaluation (nDCG/MRR/recall@k)
- Experience with vector & hybrid retrieval: ANN, dense+sparse fusion, embeddings models
- Experience building structured-extraction pipelines over messy/unstructured domain data
- Fluent in Python and comfortable with systems-level performance work
- Knowledge graphs: entity resolution, entity linking / NER, graph DBs (Neo4j), ontologies / schema design
- Owning relevance / ranking for a real product and improving it against IR metrics
- Experience with data quality, truth discovery, or trust-scoring systems
- Published work on IR, ranking, or knowledge graphs
What We Do
Cloud platform specifically designed to train AI models
