NielsenIQ

Technology

SeniorMachineLearning/DataEngineer

$130–210k ~AI est. Kuala Lumpur, Malaysia FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior Machine Learning / Data Engineer at NielsenIQ”

Industry & Context.

Technology
Full Job Description

NielsenIQ is a consumer intelligence company that delivers the Full View™, the world’s most complete and clear understanding of consumer buying behavior that reveals new pathways to growth. Since 1923, NIQ has moved measurement forward for industries and economies across the globe. We are putting the brightest and most dedicated minds together to accelerate progress. By embracing our diversity, we inspire each other to excel and create a lasting impact through our work and the people we collaborate with. NielsenIQ offers a range of products and services that leverage Machine Learning and Artificial Intelligence to provide insights into consumer behavior and market trends. This position opens the opportunity to apply the latest state of the art in AI/ML and data science to global and key strategic projects. As a Senior Machine Learning Engineer, you’ll play a key role in turning innovative ML research into scalable, real-world solutions that power global decision-making. At NiQ, we’re looking for someone to join our Tech & Durable Global Data Science team, working at the intersection of data science and engineering to transform cutting-edge research into robust, production-ready systems. If you're excited by cloud technologies, MLOps, and solving complex problems with smart, data-driven approaches, and you thrive in a collaborative, learning-focused environment, this role is for you. What You’ll Do * Build & Scale ML Systems: Design, develop, test, deploy, and maintain machine learning solutions using software engineering best practices. * Productionize Prototypes: Transform data science models into scalable, production-ready systems for real-world applications. * Own the ML Lifecycle: Implement and manage end-to-end ML workflows using MLOps practices in both cloud and on-prem environments. * Collaborate Globally: Partner with data scientists, software engineers, and product experts in cross-functional, international teams. * Drive Engineering Excellence: Develop and

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