Matching Algorithm Engineer

NewsBreak; Mountain View (CA); On-site; USD 130,000 - 170,000; Full time

Job summary

NewsBreak is seeking an experienced ML Engineer to develop algorithms that connect local consumers with businesses. This role focuses on building models for search-ranking and marketplace-matching, impacting conversion rates effectively.

We require candidates with at least 4 years in machine learning roles, specifically in ranking or matching, along with strong experimentation skills. This full-time position offers a competitive salary based on experience and education.

Qualifications

• 4+ years as an ML Engineer / Applied Scientist working on ranking, matching, dispatch, or recommendation.
• Demonstrated impact on marketplace conversion can be pointed to.
• Strong background in experimentation and causal methods for marketplaces.

Responsibilities

• Build search-ranking, marketplace-matching, and dispatch models.
• Own learning-to-rank and retrieval/recall pipelines end to end.
• Design and analyze A/B experiments to prove causal impact.

Skills

Machine Learning

Ranking algorithms

Market matching

Recommendation systems

Experimentation skills

Job description

Mountain View, California, United States

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 fulfil our mission: building the infrastructure layer for content intelligence.

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 optimisation. 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 analyse 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).

The US base salary range for this full‑time position is listed below. Pay may vary based on a number of factors including job‑related skills, level, experience, geographic location and relevant education or training. Depending on the position, the role may also be eligible for discretionary bonus and options.

We do not discriminate on the basis of any protected group status under any applicable law. This is a statement of our equal employment opportunity policy.