Local Intent Data Mining Specialist

Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech.

Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale.

Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence.

If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about

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.

• →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.

• 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.

• 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).