Senior Recommendation Engineer: Fair, Scalable Ranking

NewsBreak; Mountain View (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

NewsBreak in Mountain View, CA is seeking an experienced ML/Engineering lead to own and advance content recommender and ranking systems. You will design cross-functional ranking engineering, run large-scale experiments, and help shape fair, outcomes-driven matching between customers and service providers.

The role emphasizes strong Python, production-grade ranking pipelines, feature stores, and collaboration with product and engineering to deliver thoughtful, high-impact recommendations.

Qualifications

• 5+ years of ML or software engineering experience, including 3+ years shipping ranking systems in production.
• Built and operated ranking systems at consumer scale with candidate generation, ranking, and monitoring.
• Substantial online experimentation experience and ability to explain test results.
• Deployed uplift, causal, or counterfactual models in production or justify using non-click objectives for high-cost decisions.
• Strong Python plus at least one of Java, Scala, or Go; production experience with feature stores and streaming pipelines.

Responsibilities

• Build and own the recommendation and ranking systems for feed surfaces, from candidate generation through online experimentation and monitoring.
• Design the event-triggered engagement engine with the messaging platform team: condition detection, propensity and uplift modeling, frequency management, and holdouts.
• Build customer-to-professional matching with explicit fairness and exposure constraints to allow high-quality providers to win work.
• Define evaluation frameworks that treat downstream outcomes and negative signals as first-class objectives.
• Contribute learnings back to pricing and intent models owned by the AI team.

Skills

Machine learning

Ranking systems

Python

Online experimentation

Communication with stakeholders

Java/Scala/Go

Job description

NewsBreak in Mountain View, CA is seeking an experienced ML/Engineering lead to own and advance content recommender and ranking systems. You will design cross-functional ranking engineering, run large-scale experiments, and help shape fair, outcomes-driven matching between customers and service providers.

The role emphasizes strong Python, production-grade ranking pipelines, feature stores, and collaboration with product and engineering to deliver thoughtful, high-impact recommendations.