About the role

You will build the systems that understand what local consumers actually want — turning raw queries, behavior, and context into structured intent. This means query understanding, user-intent classification, semantic search, and the intent taxonomies and interest graphs that power discovery across local categories. You will bring LLMs into production, not the lab, to make local search and recommendations genuinely understand consumer intent.

What you'll do

• Build query-understanding, user-intent classification, and semantic-search models for local consumer demand.
• Design and grow intent taxonomies and interest graphs over local categories and merchants.
• Ship LLM-powered features into production for search and recommendations at consumer scale.
• Work with embeddings, retrieval, and NLU to connect messy consumer language to local supply.
• Define metrics and run experiments that tie intent quality to downstream conversion.

What we're looking for

• 5+ years as an Applied Scientist or ML Engineer on query understanding, intent, semantic search, or NLU.
• Production experience shipping models that serve real users — not purely offline or research work.
• Hands-on with embeddings, semantic search, intent classification, taxonomy, or interest-graph construction.
• Experience bringing LLMs into production systems.
• Comfort working at consumer-internet data scale.

Nice to have

• Background at Google Search / Ads quality, Meta, TikTok, Pinterest, DoorDash, Instacart, Amazon Search/Alexa, or Apple.
• Built a user-intent taxonomy or interest graph at a consumer internet company.
• Consumer-intent or personalization work specifically at a local platform (DoorDash, Instacart).