Machine Learning Engineer, User & Content Intelligence
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Die Stelle
Design and build a distributed feature access layer that abstracts data location and enables real-time on-device context and cloud data to be consumed via a unified API.
Develop large-scale, petabyte-scale pipelines that ingest and combine disparate data into coherent user profiles and rich content representations.
Architect data systems to transform raw data into high-value features for next-generation ML models and seamlessly integrate with training infrastructure.
Optimize for privacy and scale by extending data systems into privacy-constrained environments and applying data minimization strategies.
Partner across data systems, core compute engineering, and ML teams to ensure the right context is delivered to the right compute environment at the exact right time.
Leverage hybrid edge-cloud architectures and privacy-preserving approaches to power hyper-personalization without compromising user trust.
Develop large-scale, petabyte-scale pipelines that ingest and combine disparate data into coherent user profiles and rich content representations.
Architect data systems to transform raw data into high-value features for next-generation ML models and seamlessly integrate with training infrastructure.
Optimize for privacy and scale by extending data systems into privacy-constrained environments and applying data minimization strategies.
Partner across data systems, core compute engineering, and ML teams to ensure the right context is delivered to the right compute environment at the exact right time.
Leverage hybrid edge-cloud architectures and privacy-preserving approaches to power hyper-personalization without compromising user trust.
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