Senior Recommendation & Fairness ML Engineer

Francisco Partners

Mountain View (CA)

On-site

USD 150,000 - 300,000

Full time

14 days+
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Job summary

NewsBreak is seeking an experienced engineer to own the recommendation and ranking systems across feed surfaces, from candidate generation to online experimentation. You will design engagement triggers and a two-sided matchmaking framework with fairness considerations for service professionals.

Required are 5+ years in ML or software engineering, production ranking experience, and strong Python plus Java/Scala/Go skills. The role is based in Mountain View, CA with high-impact scope.

Qualifications

  • 5+ years of machine-learning or software engineering experience with ranking systems in production.
  • Experience shipping recommendation systems at consumer scale.
  • Strong Python and at least one of Java/Scala/Go; 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 transparent rules and evolving learning-based ranking under fairness constraints.

Skills

Python
Java
Scala
Go
Machine Learning
Recommendation systems
Online experimentation
Ranking systems
Feature stores
Streaming pipelines

Tools

JVM stack

Job description

NewsBreak is seeking an experienced engineer to own the recommendation and ranking systems across feed surfaces, from candidate generation to online experimentation. You will design engagement triggers and a two-sided matchmaking framework with fairness considerations for service professionals.

Required are 5+ years in ML or software engineering, production ranking experience, and strong Python plus Java/Scala/Go skills. The role is based in Mountain View, CA with high-impact scope.

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