Matching Algorithm Engineer

About NewsBreak

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

About the role

You will build the algorithms that connect local consumers with the right businesses at the right moment — search ranking, two-sided marketplace matching, and dispatch optimization. This is the engine of a local marketplace: learning-to-rank and retrieval pipelines, matching and dispatch models, and the relevance and recommendation systems that move marketplace conversion. If you have owned ranking or matching models that improved conversion at a marketplace, this role is the heart of the product.

What you'll do

• Build search-ranking, marketplace-matching, and dispatch models for a two-sided local marketplace.


• Own learning-to-rank and retrieval/recall pipelines end to end.


• Improve marketplace conversion through relevance, matching, and recommendation models.


• Design and analyze experiments (A/B, switchback) to prove causal impact in a marketplace setting.


• Bring modern ML/LLM techniques into ranking and matching where they add real lift.

What we're looking for

• 4+ years as an ML Engineer / Applied Scientist on ranking, matching, dispatch, retrieval, or recommendation.


• Direct work on two-sided marketplace matching or dispatch, or on search ranking with a learning-to-rank / retrieval pipeline.


• Demonstrated marketplace-conversion impact (you can point to the lift and how you measured it).


• Strong experimentation skills, including causal methods for marketplaces (e.g., switchback).


• Production ML at scale.

Nice to have

• Background at DoorDash, Uber, Instacart, Airbnb, Yelp, Nextdoor, Lyft, Amazon, or Faire.


• Relevance / matching work that connects consumers with local businesses (Yelp, Nextdoor).


• Didi / Meituan dispatch-and-matching experience, now US-based.

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