About the job
About NewsBreak
Founded in 2015, NewsBreak is a pioneering Content Intelligence platform that is redefining the content economy. With a vibrant community of over 40 million monthly active users, our flagship platform offers deeply personalized local news and information, driven by cutting-edge AI technologies, sophisticated recommendation systems, and innovative adtech solutions.
Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we take pride in being Great Place to Work® certified. Our dynamic team of technologists, product innovators, and business leaders is dedicated to tackling significant challenges at scale.
Having reached unicorn status in 2021, we are steadfast in our commitment to maintaining a high-growth trajectory through the right talent to help us realize our mission: building the infrastructure layer for content intelligence.
If you’re motivated to think big, innovate rapidly, and make a meaningful impact, we’d love to connect with you! For more information, visit www.newsbreak.com/about
About the Role
We are on the lookout for a Staff Machine Learning Engineer to spearhead technical leadership for our recommendation systems and AI initiatives.
In this pivotal position, you will set the technical direction for large-scale personalization systems, lead intricate projects across various teams, and champion the integration of AI / LLM technologies in our product capabilities and engineering workflows.
This opportunity is perfect for engineers who relish system-level thinking, enjoy mentoring others, and excel at transforming complex, ambiguous challenges into scalable solutions.
What You’ll Work On
Technical Leadership & Architecture
- Lead the design of next-generation recommendation system architectures at scale.
- Drive best practices for model lifecycle management, experimentation, and system reliability.
- Collaborate with product, infrastructure, and data teams to ensure alignment of technical strategy with business objectives.
Advanced Recommendation & AI Systems
- Oversee complex initiatives encompassing retrieval, ranking, re-ranking, and multi-objective optimization.

