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Nebius

Staff / Principal Applied AI Researcher (Agentic Search)

London
Posted 1 day ago
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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.

We are seeking a Staff or Principal Applied AI Researcher to join a fast-growing team building an agent native search platform - the web access layer for AI systems.

You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines.

We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7.

This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

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 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

Must Haves

  • 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

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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.

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Skills

Applied AI
Machine Learning
Software Engineering
Search Systems
Retrieval Systems
Ranking Systems
Recommendation Systems
Deep Learning
Transformers
Embeddings
LLM Integration
Evaluation Frameworks
Python
Go
C++

Location

London, England, United Kingdom

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