Senior ML Engineer — AI & Large-Scale Recommendations

NewsBreak; Mountain View (CA); On-site; USD 195,000 - 230,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Top-tier 401(K) with company matching

Paid time off & holidays

FSA / HSA and commuter benefits

Team activity budget

Job summary

NewsBreak in Mountain View, CA is seeking a Senior Machine Learning Engineer to advance large-scale recommendation systems and AI-powered features. You’ll own core feed, retrieval, and ranking systems serving tens of millions of users and apply cutting-edge AI methods to production problems.

This role emphasizes strong ownership, hands-on development, and delivering impactful results. Collaboration with DS/ENG teams is encouraged to scale infrastructure and experimentation.

Qualifications

• 3+ years of industry experience building ML 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.

Responsibilities

• 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.

Skills

Recommendation systems

Python

Java/Scala

ML systems

End-to-end ownership

Tools

PyTorch

TensorFlow

Spark

Distributed training

Real-time inference

Job description

NewsBreak in Mountain View, CA is seeking a Senior Machine Learning Engineer to advance large-scale recommendation systems and AI-powered features. You’ll own core feed, retrieval, and ranking systems serving tens of millions of users and apply cutting-edge AI methods to production problems.

This role emphasizes strong ownership, hands-on development, and delivering impactful results. Collaboration with DS/ENG teams is encouraged to scale infrastructure and experimentation.