Amazon
Description
The CreativeX RAPID (Real‑time Ad Personalization & Insights Development) team is seeking passionate and talented SDM to join us. CreativeX is on a mission to enable brands of all sizes and categories to create, serve, measure, and optimize creative content with ease.
Our team is responsible for tailoring the visual experience of ads to each context in real time, leveraging nueva technologies such as latent diffusion models, large language models (LLM), reinforcement learning (RL), computer vision, and related methods.
Our mission is to provide engaging, dynamically optimized creatives with low latencies both on and off Amazon for self‑service brand advertisers. We automate the customization of product creatives with real‑time catalog data while providing advertisers with the flexibility to customize their creatives according to their preferences.
Overview As an Senior Machine Learning Engineer on the CreativeX RAPID asset sourcing team, you will be responsible for building and optimizing the infrastructure that powers image and layout sourcing, while delivering actionable reporting and insights to drive creative performance.
Core Responsibilities Asset Sourcing & Pipeline Development
Design, develop, and maintain scalable ML pipelines for automated asset sourcing, including image and layout generation for selection
Own the end‑to‑end Latte pipeline implementation for asset lifecycle management across multiple stages
Implement and optimize asset indexing logic, creative variant ID generation, and asset candidate pool management
Develop algorithms to improve asset quality, diversity, and relevance for real‑time ad personalization
Collaborate with upstream asset generation teams to ensure seamless integration and data flow
Machine Learning & Optimization
Apply advanced ML techniques including computer vision, latent diffusion models, and reinforcement learning to enhance asset pool performance
Build models to predict asset performance metrics (CTR, conversion rates) and optimize asset allocation
Develop multi‑modal optimization strategies combining images, product titles, and headlines
Implement A/B testing frameworks and experimentation methodologies to validate model improvements
Reporting & Insights
Design and build comprehensive dashboards and reporting systems to track asset lifecycle stages, leakage analysis, impression share, selection rates, and CTR performance
Develop metrics and KPIs to measure asset sourcing efficiency and creative effectiveness
Provide data‑driven insights to stakeholders on asset performance, optimization opportunities, and pipeline health
Create automated alerting systems for pipeline anomalies and performance degradation
Technical Leadership & Collaboration
Mentor junior engineers and contribute to technical design reviews
Partner with AI‑Gen, AdFormat, Realtime Serving and Reporting teams to ensure alignment on technical solutions
Drive best practices for ML model development, deployment, and monitoring
Contribute to the technical roadmap and architecture decisions for the asset sourcing platform
System Performance & Scalability
Ensure reliable asset sourcing pipelines to generate creative variants for real‑time ad serving both on and off Amazon
Optimize pipeline performance to handle large‑scale asset processing
Implement monitoring and observability solutions to maintain system reliability
Design solutions that scale with growing advertiser demand and catalog complexity
Key Deliverables
Production‑ready ML models and pipelines for asset sourcing and insights
Comprehensive dashboards and reporting tools for asset performance trackingTechnical documentation and knowledge sharing with cross‑functional teams
Measurable improvements in asset quality, selection efficiency, and creative performance metrics
About the team In an ideal future, AI Gen models have evolved to a state where entire creatives are generated on the fly and precisely tailored to the immediate preferences of each shopper. We bring this vision to life by sourcing a collection of pre‑generated assets and assembling them, in real time, into personalized creative experiences for every customer.
Our mission is to improve advertiser outcomes by tailoring the visuals to each shopper and publisher. The AI space is rapidly evolving and combining optimization with Amazon’s 1P audience data will be what enables us to leapfrog the competition. Through continuous creative optimization, we expect to learn how users interact with content across a variety of context. Our upstream teams will provide us an endless variety of content, informed by our learnings, via AI generation, transformation, and deconstruction. Advertisers will receive easily digestible insights to improve their future creatives. We succeed when shoppers see creatives personalized to their intent, publishers display creatives that match their unique look and feel, and advertisers benefit from increased performance.
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Our team is responsible for tailoring the visual experience of ads to each context in real time, leveraging nueva technologies such as latent diffusion models, large language models (LLM), reinforcement learning (RL), computer vision, and related methods.
Our mission is to provide engaging, dynamically optimized creatives with low latencies both on and off Amazon for self‑service brand advertisers. We automate the customization of product creatives with real‑time catalog data while providing advertisers with the flexibility to customize their creatives according to their preferences.
Overview As an Senior Machine Learning Engineer on the CreativeX RAPID asset sourcing team, you will be responsible for building and optimizing the infrastructure that powers image and layout sourcing, while delivering actionable reporting and insights to drive creative performance.
Core Responsibilities Asset Sourcing & Pipeline Development
Design, develop, and maintain scalable ML pipelines for automated asset sourcing, including image and layout generation for selection
Own the end‑to‑end Latte pipeline implementation for asset lifecycle management across multiple stages
Implement and optimize asset indexing logic, creative variant ID generation, and asset candidate pool management
Develop algorithms to improve asset quality, diversity, and relevance for real‑time ad personalization
Collaborate with upstream asset generation teams to ensure seamless integration and data flow
Machine Learning & Optimization
Apply advanced ML techniques including computer vision, latent diffusion models, and reinforcement learning to enhance asset pool performance
Build models to predict asset performance metrics (CTR, conversion rates) and optimize asset allocation
Develop multi‑modal optimization strategies combining images, product titles, and headlines
Implement A/B testing frameworks and experimentation methodologies to validate model improvements
Reporting & Insights
Design and build comprehensive dashboards and reporting systems to track asset lifecycle stages, leakage analysis, impression share, selection rates, and CTR performance
Develop metrics and KPIs to measure asset sourcing efficiency and creative effectiveness
Provide data‑driven insights to stakeholders on asset performance, optimization opportunities, and pipeline health
Create automated alerting systems for pipeline anomalies and performance degradation
Technical Leadership & Collaboration
Mentor junior engineers and contribute to technical design reviews
Partner with AI‑Gen, AdFormat, Realtime Serving and Reporting teams to ensure alignment on technical solutions
Drive best practices for ML model development, deployment, and monitoring
Contribute to the technical roadmap and architecture decisions for the asset sourcing platform
System Performance & Scalability
Ensure reliable asset sourcing pipelines to generate creative variants for real‑time ad serving both on and off Amazon
Optimize pipeline performance to handle large‑scale asset processing
Implement monitoring and observability solutions to maintain system reliability
Design solutions that scale with growing advertiser demand and catalog complexity
Key Deliverables
Production‑ready ML models and pipelines for asset sourcing and insights
Comprehensive dashboards and reporting tools for asset performance trackingTechnical documentation and knowledge sharing with cross‑functional teams
Measurable improvements in asset quality, selection efficiency, and creative performance metrics
About the team In an ideal future, AI Gen models have evolved to a state where entire creatives are generated on the fly and precisely tailored to the immediate preferences of each shopper. We bring this vision to life by sourcing a collection of pre‑generated assets and assembling them, in real time, into personalized creative experiences for every customer.
Our mission is to improve advertiser outcomes by tailoring the visuals to each shopper and publisher. The AI space is rapidly evolving and combining optimization with Amazon’s 1P audience data will be what enables us to leapfrog the competition. Through continuous creative optimization, we expect to learn how users interact with content across a variety of context. Our upstream teams will provide us an endless variety of content, informed by our learnings, via AI generation, transformation, and deconstruction. Advertisers will receive easily digestible insights to improve their future creatives. We succeed when shoppers see creatives personalized to their intent, publishers display creatives that match their unique look and feel, and advertisers benefit from increased performance.
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