Machine Learning Engineer – Search & Retrieval Systems

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Описание

About Wizard Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust. The Role We're looking for a Machine Learning Engineer to own the search and retrieval systems that power Wizard's AI shopping agent. Every product recommendation starts with finding the right candidates from millions of listings – fast, relevant, and adapted to the query at hand. You'll own how we retrieve, rank, and adapt search behavior, from the retrieval pipeline through ranking models to the business logic that shapes the final result set. Unlike traditional search engineering – our search pipeline adapts its behavior per query, learns from production signals, and serves a conversational agent where intent evolves across turns. You'd own both the systems that execute search and the applied ML that makes those systems smarter over time. What You’ll Do Own and evolve the hybrid search pipeline – lexical retrieval, dense vector search, reciprocal rank fusion, and multi-stage reranking on Elasticsearch Build and train adaptive retrieval models – lightweight classifiers and ranking models that configure search behavior per query, per category, per context (source routing, per-attribute boost prediction, filter mode decisions) Design and productionize the learning-to-rank system – from feature engineering through model training (LightGBM, ONNX) to production deployment and A/B evaluation Build the search feedback loop – instrument and integrate behavioral signals (CTR, conversions, add-to-cart) into ranking and retrieval as features for LTR, reward signals for adaptive retrieval, and inputs for search-side person

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