Senior Local Intent Data Scientist - AI & Semantic Search

Francisco Partners

Mountain View (CA)

On-site

USD 112,000 - 293,000

Full time

14 days+
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Job summary

NewsBreak is hiring a Senior Applied Scientist/ML Engineer to build systems that understand what local consumers want, turning raw queries and behavior into structured intent. You’ll bring LLMs into production to power local search and recommendations at scale.

The role requires 5+ years in query understanding, semantic search, or NLU, with hands-on experience shipping models serving real users and working with embeddings and interest graphs at consumer-internet scale.

Qualifications

  • 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.
  • 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.

Responsibilities

  • 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.

Skills

Applied Scientist
ML Engineer
Query understanding
Semantic search
NLU
Embeddings
LLMs in production
Consumer-internet scale

Job description

NewsBreak is hiring a Senior Applied Scientist/ML Engineer to build systems that understand what local consumers want, turning raw queries and behavior into structured intent. You’ll bring LLMs into production to power local search and recommendations at scale.

The role requires 5+ years in query understanding, semantic search, or NLU, with hands-on experience shipping models serving real users and working with embeddings and interest graphs at consumer-internet scale.

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