Principal Applied AI Researcher — Agentic Retrieval

Nebius; United States; On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Competitive compensation

Career growth opportunities

Flexibility and ownership

Collaborative culture

Impactful AI projects

International environment

Job summary

Nebius is building a full-stack AI cloud platform and is seeking a Staff or Principal Applied AI Researcher to own key parts of our applied AI research direction, focusing on agent native retrieval and scalable web data reasoning for AI systems.

You will design and implement retrieval architectures, experiment with embeddings and ranking methods, and collaborate with engineers to push production-grade AI capabilities at scale.

Qualifications

• 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.

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.

Skills

Applied AI

ML Systems

Search & Retrieval

Transformers & Embeddings

LLM Integration

Evaluation Frameworks

Python

Go/C++

Tools

Go

C++

Job description

Nebius is building a full-stack AI cloud platform and is seeking a Staff or Principal Applied AI Researcher to own key parts of our applied AI research direction, focusing on agent native retrieval and scalable web data reasoning for AI systems.

You will design and implement retrieval architectures, experiment with embeddings and ranking methods, and collaborate with engineers to push production-grade AI capabilities at scale.