Senior Product Manager: Recall

Key details

• Set a unified multi-quarter roadmap and strategy across the Machine Learning & Recall and Query teams, ensuring query understanding and candidate generation evolve together
• Lead the Query team in tokenization, spell correction, entity extraction, intent classification, and LLM-assisted query parsing across multiple languages
• Lead the Machine Learning & Recall team in evolving candidate generation architecture, combining traditional keyword search with dense embeddings, vector retrieval, and hybrid recall models
• Own measurable lift in search-attributed conversion, revenue per visit, and GMV across retail customer verticals
• Work with ML researchers, data scientists, and software engineers to take SOTA models from research to low-latency, cost-effective production systems
• Make data-backed decisions balancing model complexity, accuracy, inference latency, compute costs, and real-time execution constraints
• Establish robust offline and online measurement systems to evaluate retrieval precision and query understanding accuracy against customer revenue outcomes
• Ensure candidate product sets and query context flow cleanly into downstream ranking and search quality models without signal loss
• Lead technical triage for query interpretation or retrieval anomalies, building durable automated fixes rather than one-off patches
• Company mission
• Information not specified