Salary
💰 $170,000 - $200,000 per year
About the role
- Define and lead the strategy for search and embeddings, shaping how users retrieve and ground information from large scale, multimodal video corpora
- Drive execution across research, infra, and product teams, owning the lifecycle from model design through system integration and user impact
- Engage deeply with technical users such as ML engineers, search architects, and infra teams to inform product direction and validate performance against production needs
- Establish rigorous evaluation standards for search quality, latency, cost, and reranking performance, and partner with ML to set strong goals and meet them
- Translate model innovations into product leverage, crafting developer friendly APIs, Playground features, and workflows that showcase our model’s full potential
Requirements
- Bring 5+ years of product management experience, including at least 1 years of owning search, retrieval, RAG, or embeddings in ML driven systems
- Have strong technical fluency and can read ML papers, understand embedding architectures, and collaborate easily with researchers and platform engineers
- Have shipped infrastructure or developer facing products, especially involving semantic search, dense or sparse or hybrid retrieval, vector databases, or cross encoder ranking
- Thrive in zero to one environments, where category conventions don’t exist and your product decisions shape the frontier
- Balance vision with execution rigor: you zoom out to define what the future should look like and zoom in to ship quality, performant features with urgency and care