Senior Machine Learning Engineer, Recommendation & AI Applications
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 fulfill our mission: building the infrastructure layer for content intelligence. If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about About the Role We are looking for a Senior Machine Learning Engineer to help evolve our large-scale recommendation systems and apply AI / LLM technologies to real-world production problems. You will work on core feed, retrieval, and ranking systems serving tens of millions of users, while also participating in AI-driven innovation projects that explore new ways to improve content discovery, personalization, and developer productivity. This role is ideal for engineers who enjoy strong individual ownership, hands-on development, and translating ideas into reliable systems. What You’ll Work On Large-Scale Recommendation Systems Design, build, and iterate on high-throughput, low-latency recommendation systems powering NewsBreak’s core feeds. Improve retrieval, ranking, and multi-objective optimization to balance engagement, retention, content quality, and business metrics. Own systems from offline training → online inference → A/B experimentation → metric analysis. Identify and resolve issues related to data quality, model drift, and system performance in production. AI & LLM Applications Apply LLMs and foundation models to recommendation-related problems such as content understanding, user intent modeling, and feature generation. Prototype quickly, validate with experiments, and push successful ideas into production. AI-Driven Development Embrace AI-assisted development workflows, including LLM-powered coding, debugging, and analysis. Apply AI across feature ideation, prototyping, and experiment analysis. 0 → 1 Innovation Contribute to 0–1 AI-powered projects, helping take ideas from early exploration to MVP and production. What We’re Looking For Minimum Qualifications - 3+ years of industry experience building machine learning or recommendation systems in production. - Strong understanding of recommendation system fundamentals (ranking, embeddings, user/item modeling, experimentation). - Strong coding skills with Python / Java / Scala, and experience with PyTorch or TensorFlow. - Experience working ...