Staff ML Engineer - Search & Reco - m/w/d

Staff ML Engineer — Search & Reco - m/w/d

Join one of the world's largest and most innovative digital real estate tech companies.

Backed by global investment leaders KKR and CPP Investments, AVIV Group is reshaping the way people across Europe buy, sell, rent, lease, and value real estate.

With a strong presence in Europe, we power some of the region's most recognized digital real estate platforms across various countries – including Immoweb, SeLoger, and Meilleurs Agents (France's leading real estate valuation platform), alongside immowelt and Homeday (one of Germany's fastest-growing PropTech companies). Our European footprint is complemented by our dynamic tech and engineering hubs in Romania and Croatia.

Our mission? We simplify life's most important transactions. By combining data, technology, and human expertise, we empower millions of people to find their perfect home!

Help us shape the future of real estate.

Role summary You'll own ranking and retrieval problems across AVIV Group's real-estate platforms — from query understanding to re-ranking to production on-call. Every model decision ships with an explanation, and you're one of the people the team turns to when a metric win can't be explained.

What you'll do

- Design, train, and ship models for search relevance, ranking, and recommendations, from candidate retrieval through re-ranking to business-rule layers.

- Set the experimental standard: offline evaluation that predicts online behavior, well-designed A/B tests, and the judgment to kill a win that can't be explained.

- Own the architecture of the systems you touch — make build-vs-adopt calls, hold the line on reproducibility and observability.

- Operate what you ship: serving, monitoring, SLOs, and a share of the team's on-call rotation.

- Lead the move toward LLM-augmented search — query understanding, semantic retrieval, conversational surfaces — separating production-ready work from demos.

- Mentor through design reviews and technical writing that make good decisions repeatable.

- Work directly with product on what to optimize for, and push back with evidence when a target is measurable but wrong.

What you bring

- 8+ years of engineering experience, with at least 3 shipping ML systems to production at meaningful scale.

- Hands-on experience designing ranking/retrieval/recommendation systems across the full funnel: candidate generation, feature engineering, model architecture, re-ranking.

- Experience diagnosing offline/online divergence and changing a team's evaluation practice.

- Strong engineering fundamentals: production-quality code, reliable data pipelines, reproducibility as a baseline.

- A track record of technical influence beyond your own output.

- Clear communication about uncertainty, including "we don't know yet."

Nice to have

- LLM-based search features in production (semantic retrieval, embeddings at scale, RAG, query understanding) with evaluation to back the claims.

- Learning-to-rank, vector search, or candidate-generation systems at high scale.

- Marketplace or classifieds domain background.

- Geospatial features in ranking.