about 23 hours ago
Amsterdam, Netherlands +2 more
Staff+ / Senior
Responsibilities
- Drive applied research across retrieval, ranking, and agent-centric search systems.
- Design and improve multi-stage retrieval pipelines, including query understanding, rewriting, and reranking.
- Develop approaches for grounding LLMs using real-time web data.
- Define and implement evaluation methodologies and quality metrics for agent-native search.
- Lead experimentation on modern retrieval techniques such as hybrid search and embedding-based systems.
- Work closely with engineering teams to bring research into production at scale.
- Analyze trade-offs across relevance, latency, and cost in large-scale systems.
- Contribute to long-term research and product direction.
- Mentor engineers and researchers and raise the technical bar of the team.
Requirements
- 8+ years of experience in applied AI, machine learning, or software engineering.
- Strong track record of shipping ML or AI systems into production, not purely research.
- Deep experience in retrieval, ranking, search relevance, or recommendation systems.
- Strong understanding of modern deep learning approaches including transformers and embeddings.
- Experience working with LLM-integrated systems or knowledge-intensive AI applications.
- Hands-on experience designing evaluation frameworks and defining meaningful metrics.
- Strong programming skills in Python, Go, or C++.
- Ability to operate in a product-driven, fast-moving environment.
- Strong ownership and ability to drive ambiguous problems end-to-end.
Benefits
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Flexible working arrangements.
- A dynamic and collaborative work environment that values initiative and innovation.
Tech Stack
C++GoPython
Categories
AI & MLData Science