Staff Machine Learning Engineer - Search and Recommendation

About the Company

AVIV Group is a leading digital real estate technology company with a strong presence across Europe. Supported by global investors like KKR and CPP Investments, the group operates well-known platforms such as Immoweb, SeLoger, Meilleurs Agents, immowelt, and Homeday. Through a combination of data, technology, and expertise, AVIV Group simplifies real estate transactions and helps millions find their ideal homes. The company's tech hubs are located in Romania and Croatia.

Role Overview

The Staff Machine Learning Engineer will take full ownership of ranking and retrieval challenges on AVIV's real estate platforms. Responsibilities include end-to-end model development from query understanding to re-ranking, ensuring models provide interpretable results, and production support. The role involves setting standards in experimentation, architectural decisions, monitoring, and integrating large language model (LLM)-enhanced search capabilities.

Key Responsibilities

• Develop, train, and deploy models targeting search relevance, ranking, and recommendation tasks covering stages from initial candidate retrieval through re-ranking and business rule integration.
• Establish and uphold rigorous evaluation standards including offline metrics predictive of online user behavior, well-planned A/B testing, and readiness to discard inconclusive improvements.
• Make architectural decisions involving build versus adopt choices, with a strong emphasis on reproducibility and system observability.
• Manage production systems including serving infrastructure, monitoring, service-level objectives, and participate in on-call rotations.
• Drive adoption of LLM-based techniques for enhanced search, including semantic retrieval, query understanding, and conversational interfaces, distinguishing production-grade solutions from prototypes.
• Mentor peers through conducting design reviews and authoring technical documentation that promotes consistent decision-making.
• Collaborate closely with product teams to define optimization targets and challenge measurable yet misaligned goals based on evidence.

Required Qualifications

• Minimum of eight years of software engineering experience, with at least three years dedicated to deploying machine learning systems at scale.
• Proven expertise in designing ranking, retrieval, and recommendation engines throughout all funnel stages such as candidate generation, feature engineering, model development, and re-ranking.
• Experience identifying and resolving discrepancies between offline and online evaluation metrics, and implementing improved evaluation practices team-wide.
• Strong software engineering skills including writing production-quality code, building robust data pipelines, and ensuring reproducibility of results.
• Demonstrated technical leadership with influence beyond individual project deliverables.
• Ability to communicate uncertainties clearly, acknowledging unknowns where appropriate.

Additional Preferred Experience

• Practical implementation of LLM-powered search features including semantic retrieval, large-scale embedding handling, retrieval augmented generation, and query comprehension along with their evaluation.
• Knowledge of learning-to-rank techniques, vector-based search, and candidate generation at scale.
• Background working with marketplaces or classified advertisement platforms.
• Experience incorporating geospatial data into ranking algorithms.