Senior Machine Learning Engineer, Recommendation & AI Applications

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 with large-scale data and ML systems (e.g., Spark, distributed training, real-time inference). - Ability to own features end-to-end and deliver measurable business impact.

Bonus / Plus Qualifications - Production experience applying AI or LLMs to recommendation systems. - Experience contributing to 0 → 1 AI or ML-driven products. - Familiarity with AI-assisted development tools and workflows.