Nebius B.V. logo
Est. Monthly
Estimated €3,828 - €6,000
Posted August 26, 2026 · 0 days agoLast seen August 26, 2026Est. expiry September 30, 2026

Applied AI Researcher

Staff / Principal Applied AI Researcher (Agentic Search)
Remote - Europe
Remote · Technology
Full-time · Senior
English
No People Management
8 years experience
How this salary compares
Salary Context: Applied AI Researcher

Hover or tap a row for full statistics (EUR / month on this chart).

Salary analysis

Compared with the selected benchmark ("Company in Remote - Europe"), this listing's salary midpoint is about 89% lower. The offer sits below the benchmark range (€1,667–€6,000). The listed pay band (€319–€500) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 6 comparable listings.

Monthly salary comparison for Applied AI Researcher
MarketLower bound (25th percentile)MedianUpper bound (75th percentile)
All roles in Remote - Europe€1,978/per month€4,914/per month€13,713/per month
Company in Remote - Europe€1,667/per month€2,056/per month€6,000/per month
This job's pay range — not quoted in ad (Senior)€319/per month€410/per month€500/per month
About the role

What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely 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 technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proved 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 similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact 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.

Job Details

Responsibilities

  • Drive applied research and technical direction across retrieval and ranking systems
  • Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval)
  • Develop methods for grounding LLMs in real time web data at scale
  • Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks
  • Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production
  • Analyse trade-offs across relevance, latency, and cost at scale
  • Work closely 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 technical bar of the team

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 similar
  • Ability to operate in a fast moving, product driven environment with high ownership and autonomy

Skills & Technologies

PythonGoC++TransformersEmbeddingsLLMRetrievalRerankingEmbeddingsHybrid search
Seen 11 hours agoPartial Schema
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