Search and Recommendations Engineer

Gem.app is one of the largest online search engines for vintage and second-hand clothing. We aggregate products from eBay, Etsy, Depop, Poshmark, Grailed, Vestiaire Collective, and hundreds of independent stores into a seamless mobile and web experience. We process over a million listings daily to help users find the gems they are looking for - wherever they are. Role Overview We're seeking a full time Search and Recommendations Engineer to improve our keyword-based search with machine learning approaches and enhance personalization. You'll take the lead on exploring, implementing, and evaluating solutions that improve search relevance and deliver recommendations tailored to user interests. The ideal candidate has a broad and deep understanding of the different search approaches, as well as practical experience implementing them at a large-scale. Responsibilities Identify and propose solutions aligned with requirements and resources. Plan project roadmap and milestones. Translate insights into actionable recommendations and effectively communicate them to the rest of the team. Design the architecture and implement solutions end-to-end. Monitor the performance of your solutions using A/B tests and iteratively improve them. Requirements Experience with search methods (e.g., BM25, vector, hybrid). Experience improving search relevance with user signals (e.g., clicks, likes), and techniques (e.g., disambiguation, knowledge graphs, deduplication). Experience improving search experience through interactive refinements (e.g., suggestions, facets). Experience implementing recommendation algorithms or feeds. Curiosity about the problem domain and sense of ownership. Analytical mindset and ability to work independently. ElasticSearch, Python (ML libraries), TypeScript/Node.js, Postgres. Bonus skills AWS/cloud experience. Training or fine-tuning Machine Learning models.

Gem.app is one of the largest online search engines for vintage and second-hand clothing. We aggregate products from eBay, Etsy, Depop, Poshmark, Grailed, Vestiaire Collective, and hundreds of independent stores into a seamless mobile and web experience. We process over a million listings daily to help users find the gems they are looking for - wherever they are.