ML Engineer: Search, Personalization & Recommendations

NewsBreak; Mountain View (CA); On-site; USD 190,000 - 300,000; Full time

Job summary

NewsBreak in Mountain View, CA is seeking a Machine Learning Engineer to build intelligent systems that connect consumers with relevant local content and services. You will work across search, recommendation, ranking, retrieval, user-intent understanding, personalization, and marketplace matching.

Depending on your background, you may focus on improving search and recommendation relevance or building models that better match users with local content and services.

Qualifications

• Experience building ML systems for search, recommendation, ranking, or NLP.
• Strong coding skills in Python, Java, or C++ and ability to work with large data.
• Familiarity with ML fundamentals and model evaluation in production.

Responsibilities

• Build and improve ML models for search, recommendation, ranking, retrieval, and personalization.
• Understand user queries and context to drive better recommendations.
• Apply embeddings, NLP, and LLM techniques to connect demand with content and services.
• Develop end-to-end ML pipelines from data prep to online serving and monitoring.
• Collaborate with product, engineering, and data teams to translate business needs into scalable ML solutions.
• Design experiments to measure model quality and product impact.
• Improve relevance, engagement, and marketplace efficiency.

Skills

ML systems

Python

Java

C++

Data structures

NLP/LLM

Large-scale data

Tools

PyTorch

TensorFlow

Spark

Kubernetes

Job description

NewsBreak in Mountain View, CA is seeking a Machine Learning Engineer to build intelligent systems that connect consumers with relevant local content and services. You will work across search, recommendation, ranking, retrieval, user-intent understanding, personalization, and marketplace matching.

Depending on your background, you may focus on improving search and recommendation relevance or building models that better match users with local content and services.