2 months ago
Amsterdam, NetherlandsStaff+
Responsibilities
- Drive applied research and technical direction across retrieval and ranking systems.
- Design and evolve multi-stage retrieval architectures, including query understanding, rewriting, reranking, and iterative retrieval.
- Develop methods for grounding LLMs in real-time web data at scale.
- Define and implement evaluation paradigms and metrics for agentic systems.
- Lead experimentation with embeddings, hybrid search, and reranking, and bring successful approaches into production.
- Analyze trade-offs across relevance, latency, and cost at scale.
- Work with engineering to deploy systems in high-throughput, low-latency environments.
- Own ambiguous problems end to end and contribute to product and research direction.
- Mentor engineers and help raise the team’s technical bar.
Requirements
- 8+ years of experience in applied AI, ML, or software engineering.
- Proven track record of shipping ML or AI systems to production at scale.
- Deep experience with search, retrieval, ranking, recommendation systems, or assistants.
- Strong understanding of modern deep learning, especially transformers and embeddings.
- Experience with LLM-integrated or knowledge-intensive systems.
- Experience designing evaluation frameworks and metrics for ML systems.
- Strong programming skills in Python and at least one of Go, C++, or a similar language.
- Ability to work in a fast-moving, product-driven environment with high ownership and autonomy.
- Experience with large-scale search or recommendation systems is preferred.
- Background in agentic AI systems, including agents, tool use, or autonomous workflows, is preferred.
- Experience with RAG, multi-step retrieval, or tool use is preferred.
- Publications, open-source work, or similar evidence of technical depth and impact is preferred.
Benefits
- Competitive compensation, with no specific amount stated.
- Career growth and learning opportunities.
- Flexibility and ownership.
- Collaborative and innovative culture.
- Opportunity to work on impactful AI projects.
- International environment and talented teams.
- Applicants must be authorized to work in the country where they apply and provide proof of employment eligibility.
Categories
About Nebius
Nebius builds a full-stack AI cloud offering GPU compute, storage, and tools for training and deploying ML models for startups, enterprises, and research labs. It sells consumption-based cloud infrastructure (IaaS/PaaS) and managed services tailored to generative AI workloads, including large-scale model training and inference. The company is headquartered in Amsterdam and operates as an independent provider.