AI / ML Engineer II / III

About the role

As a Machine Learning Engineer, you will take a leading role in designing and building the end-to-end systems that power intelligent products at Nielsen. You will own complex projects from conception to deployment, making critical design and architectural decisions. This is a high-impact role for a hands-on engineer who can handle ambiguity, mentor others, and deliver robust, scalable ML solutions.

Responsibilities

• Own the complete lifecycle of machine learning systems, including problem formulation, data
• pipeline design, model development, deployment, and monitoring.
• Make key architectural and design decisions to ensure our ML systems are scalable, reliable, and
• efficient.
• Navigate project requirements, creating clear plans of action and defining technical roadmaps.
• Optimize complex data pipelines and ML models for performance.
• Mentor junior engineers on the team, fostering their growth and ensuring high technical
• standards.
• Act as the technical point of contact for your projects, managing communication with product
• managers and other stakeholders.
• Cultivate a team environment focused on continuous learning, where innovative audience
• measurement methodologies are developed and refined through collaborative effort

Requirements

• Master's or Bachelor's degree in Engineering, Mathematics, Statistics or a related field.
• A proven track record of owning and shipping production machine learning systems.
• Deep expertise in classification models, regression models, anomaly detection, boosted models,
• deep learning and simulation problems, particularly with large datasets.
• Deep expertise in ML concepts, data engineering, and MLOps practices.
• Proficiency in Python and SQL.
• Must have deployed E2E ML systems by automating training and inference pipelines.
• Hands-on experience with distributed computing frameworks like Apache Spark.
• Experience with workflow orchestration tools (e.g., Airflow) and MLOps.

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Company Intel

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