ML Engineer - Search & Personalization with Equity

NewsBreak; United States; On-site; USD 190,000 - 300,000; Full time

Job summary

NewsBreak is seeking a Machine Learning Engineer to build intelligent systems that connect users with local information, businesses, and services. You will work on search, recommendation, ranking, retrieval, and marketplace matching, with opportunities to focus on consumer demand or improving relevance and user experience.

You will take ML solutions from problem definition to production deployment, collaborating with product, engineering, and data teams to deliver measurable value for real users

Qualifications

• Experience building ML, data mining, search, or NLP systems.
• Strong programming skills in Python, Java, or C.
• Ability to translate business problems into scalable ML solutions.

Responsibilities

• Build and improve ML models for search, recommendation, ranking, retrieval, matching, and personalization.
• Develop systems that understand user queries, behaviors, preferences, and context.
• Apply embeddings, NLP, LLMs, and modern retrieval techniques to connect demand with content or services.
• Build and optimize end-to-end ML pipelines from data prep to online serving and monitoring.
• Collaborate with product, engineering, and data teams to define problems and translate needs into scalable solutions.
• Design and analyze online and offline experiments to measure model quality and product impact.
• Improve outcomes like relevance, engagement, conversion, retention, and marketplace efficiency.
• Explore new ML and LLM techniques and bring them into production.

Skills

Machine learning

Python

Java

C

Data structures

Tools

PyTorch

TensorFlow

Spark

Kubernetes

Job description

NewsBreak is seeking a Machine Learning Engineer to build intelligent systems that connect users with local information, businesses, and services. You will work on search, recommendation, ranking, retrieval, and marketplace matching, with opportunities to focus on consumer demand or improving relevance and user experience.

You will take ML solutions from problem definition to production deployment, collaborating with product, engineering, and data teams to deliver measurable value for real users