Product Data and Matching Engineer

Role overview Build the product matching and data quality layer for ecommerce listings gathered from many online shops. The work focuses on recognizing when differently titled listings represent the same product, distinguishing offer types such as new and resale, and helping agents receive results that fit their requests.

Responsibilities - Match listings across shops using brand, model, variant and identifiers such as GTIN or MPN. - Combine embeddings or language models with rules and evaluation sets to keep matching quality measurable. - Classify offers by condition, seller type and country so results can be filtered appropriately. - Build evaluation sets from real queries and track match precision and recall over time. - Use quality findings to guide improvements to extraction, search and offer ranking.

Requirements - At least three years in data engineering, search or applied machine learning involving messy real-world data. - Strong Python and SQL skills. - Experience creating evaluation sets and measuring data or model quality. - Practical experience with LLM APIs or embeddings. - Clear written English.

Nice to have - Experience with ecommerce catalogs, product taxonomies or entity resolution. - Familiarity with vector search or ranking.