AI Growth Engineer: Personalization, Data Pipelines & Ads

NewsBreak; Mountain View (CA); Hybrid; USD 135,000 - 155,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Paid time off

FSA/HSA benefits

Team activity budget

Job summary

NewsBreak is seeking a curious software engineer to join the Corporate Ventures and AI Operations team. You will work at the intersection of backend engineering, ML infrastructure, and revenue systems, building pipelines and services powering our ads platform, and contributing to recommendation systems with low latency production data.

You will help instrument personalization, maintain data pipelines, and collaborate with business stakeholders to ship production systems transforming data into

Qualifications

• Bachelor's or Master's degree in CS, software engineering, or a related field
• Strong fundamentals in data structures, algorithms, and system design
• Proficiency in Python, Java, Scala, or Go with SQL knowledge
• Experience with data pipelines, backend services, or applied software systems
• Exposure to distributed data processing concepts (Spark, Hive) is a plus
• Understanding of A/B testing and experimental design

Responsibilities

• Build and maintain data pipelines and backend services for ads, events, and engagement data
• Write clean, well-tested code and collaborate with senior engineers on data APIs
• Contribute to data architecture for ad-tech integrations and monetization surfaces
• Develop monitoring, instrumentation, and automated data quality checks
• Support revenue operations tooling and quota/commission systems

Skills

Python

Java

Scala

Go

SQL

Education

Bachelor's or Master's degree in CS/Software Engineering

Tools

Spark

Hive

Job description

NewsBreak is seeking a curious software engineer to join the Corporate Ventures and AI Operations team. You will work at the intersection of backend engineering, ML infrastructure, and revenue systems, building pipelines and services powering our ads platform, and contributing to recommendation systems with low latency production data.

You will help instrument personalization, maintain data pipelines, and collaborate with business stakeholders to ship production systems transforming data into