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Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com.
WWR&R is an agile, innovative organization dedicated to 'making zero happen' to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing novel products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world

We have an eye to the future - we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon - Returns & ReCommerce.
Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus.
You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process

You can develop scalable, high-availability solutions to solve complex and broad business problems.
We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth.
Amazon is earth's most customer-centric company and through WWRR&S, the earth is our customer too

Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
Key job responsibilities
3+ years managing software development or machine learning engineering teams, including hiring, mentoring, and developing technical talent
4+ years architecting large-scale model hosting infrastructure, low-latency inference runtimes, and end-to-end model management workflows
2+ years of hands-on programming experience in Java, C++, Python, or related languages, with a focus on writing highly optimized, production-ready code
Proficiency in Natural Language Processing (NLP), Computer Vision (CV), and core machine learning (ML) engineering design patterns.
Proven experience in Operational Excellence (DevOps/MLOps), Data Engineering/Pipelines, and Cross-Functional Leadership (collaboration with Applied Science and Product teams).
Excellent oral and written communication skills, with the ability to communicate complex system architectures, MLOps strategies, and AI solutions to all levels of the organization
About the team
The Worldwide Returns & Recommerce (WWRR) Science & Tech team owns a complex multi-disciplinary scope: building the AI and machine learning infrastructure that powers Amazon's global reverse logistics. Operating across the Online Return Center (ORC), Item Grading, and Transportation verticals, we deploy NLP, Computer Vision (CV), and Classical ML to solve high-stakes engineering and asset-optimization challenges at scale.
Returns are growing in volume and complexity. We meet this challenge by engineering production AI/ML platforms that automate decision-making, maximize financial recovery, and optimize processing efficiency from the exact moment a customer initiates a return through every physical touchpoint.
By joining this team, you will design the high-throughput model hosting infrastructure, intelligent grading pipelines, and low-latency inference runtimes that directly accelerate the R&R flywheel-transforming global recommerce into a world-class operation.