Sr. MLE, Creative-X, Amazon Advertising, Creative-X
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 nouvelle technologies such as latent diffusion models, large language models (LLM), reinforced 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.
Key Job Responsibilities
Senior Machine Learning Engineer - Asset Sourcing & Insights
Overview
As a 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 tracking
- Technical 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.
Basic Qualifications
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
Preferred Qualifications
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
About Amazon
Amazon is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence. Founded in 1994 by Jeff Bezos, Amazon's mission is to be Earth's most customer-centric company, Earth's best employer, and Earth's safest place to work.
Our Mission
Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to deliver customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, and many other pioneering products and services.
What We Do
We work to provide broad selection, value, and convenience across a range of customer experiences, including online shopping, cloud computing, streaming, and advertising. We operate a lot like a set of startups, embracing invention and creating stores, devices, and services that our customers will use, share, and love.
Every day, we invent on behalf of our customers, partners, and communities. We are focused on delivering a constellation of devices, services, and experiences that empower our customers to stay connected, safe, informed, productive, educated, and entertained. Our Operations and award-winning Customer Service teams are at the heart of Amazon's mission to be Earth's most customer-centric company.
April 10, 2026
5-7 business days
After submission
- •Role explicitly requires applied AI techniques (latent diffusion, LLMs, RL, computer vision) used to generate and optimize creative assets.
- •Strong workflow integration: end-to-end ML pipelines, real-time serving, asset lifecycle management, monitoring, and alerting are core responsibilities.
- •High tool proficiency and production focus: building models to predict CTR/conversions, A/B experimentation, dashboards, and operationalization are required.
This is a strong senior production ML role at a stable, well-resourced company with explicit salary range, high-impact responsibilities, and exposure to advanced ML methods. Foundational needs (pay and stability) are largely met; the posting signals good opportunities for esteem and technical growth. Gaps include role clarity (IC vs manager), missing explicit benefits/total comp details, and unclear operational expectations (on-call/availability) and flexibility. Candidates should clarify reporting, day-to-day responsibilities, on-call expectations, and concrete development support during interviews.
- •Role ambiguity: description contains conflicting language ('seeking passionate and talented SDM' vs title 'Sr. MLE') — unclear whether managerial duties are required.
- •Benefits/total compensation components are not specified (no explicit mention of health insurance, 401(k)/matching, equity/RSUs, or bonus structure) despite an explicit base range.
- •On-site requirement is strict ('on-site') but relocation, flexible work, or hybrid options are not described — could be limiting for candidates.
- •Clear, senior-level role focused on production ML systems with strong technical leadership responsibilities.
- •Explicit annual compensation range: $151,300 - $261,500.
- •Work focuses on cutting-edge ML areas (latent diffusion models, LLMs, RL, computer vision) and real-time low-latency serving — strong technical growth potential.
- •The description alternates between 'Sr. MLE' and 'seeking passionate and talented SDM' — is this position an individual-contributor Senior Machine Learning Engineer or a Software Development Manager? What percentage of the role is people management versus hands-on engineering?
- •Can you describe the team's current size and structure (number of engineers, ML researchers, product/PM partners) and who this role reports to? What are the immediate projects or priorities for the first 3–6 months?
- •What are the on-call, SLA, or availability expectations for this role (e.g., on-call rotations, weekend support) given the emphasis on real-time low-latency serving and pipeline reliability?
Location
Salary Range
$151k - $262k
Employment Type
Full-time
Experience Level
Senior
Posted
January 10, 2026 (2 weeks ago)
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