Amazon
Senior Applied Scientist, Mechatronics & Sustainable Packaging (MSP)
Amazon, Bellevue, Washington, United States, 98009
Applied Scientist Opportunity
Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? The Mechatronics & Sustainable Packaging (MSP) team is seeking an experienced and senior Applied Scientist who will join a team of experts in the field of Machine Learning, Statistics, Operations Research, Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. The MSP team owns mission-critical automation and packaging solutions that impact billions of customer shipments annually across Amazon's WW marketplaces. We manage billions in material spend and pack labor costs while driving significant reductions in carbon emissions. Our team is revolutionizing e-commerce through advanced packaging automation, innovative sortation technology, and sustainable solutions. We're dramatically reducing single-use plastics across our network while developing next-generation automated solutions that can handle the majority of our packaging needs. We're also transforming our supply chain through strategic investments in paper manufacturing and innovative materials, driving both substantial cost savings and environmental benefits. This is an exciting opportunity to work on large-scale automation challenges that directly impact customer experience, operational efficiency, and environmental sustainability at one of the world's largest e-commerce companies. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven't been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, operations research, statistics, big data, and building scalable solutions, this role is for you. Key job responsibilities: Develop advanced AI models by extracting predictive features from multiple data sources (product/packaging images, product descriptions, sensor data, geospatial data) to forecast package-related damages and optimize packaging decisions based on customer preference prediction Build causal inference model to capture the downstream impacts of different packaging designs and delivery experience Leverage generative AI technologies to develop scalable solutions for automated product compatibility and safety assessments (e.g., evaluating product shipping compatibility, safety requirements, and packaging configurations) Develop and implement computer vision solutions to automate packaging workflows and detect product/packaging defects in real-time operations Design and implement robotic control algorithms to optimize machine efficiency and meet diverse business objectives
Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? The Mechatronics & Sustainable Packaging (MSP) team is seeking an experienced and senior Applied Scientist who will join a team of experts in the field of Machine Learning, Statistics, Operations Research, Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. The MSP team owns mission-critical automation and packaging solutions that impact billions of customer shipments annually across Amazon's WW marketplaces. We manage billions in material spend and pack labor costs while driving significant reductions in carbon emissions. Our team is revolutionizing e-commerce through advanced packaging automation, innovative sortation technology, and sustainable solutions. We're dramatically reducing single-use plastics across our network while developing next-generation automated solutions that can handle the majority of our packaging needs. We're also transforming our supply chain through strategic investments in paper manufacturing and innovative materials, driving both substantial cost savings and environmental benefits. This is an exciting opportunity to work on large-scale automation challenges that directly impact customer experience, operational efficiency, and environmental sustainability at one of the world's largest e-commerce companies. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven't been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, operations research, statistics, big data, and building scalable solutions, this role is for you. Key job responsibilities: Develop advanced AI models by extracting predictive features from multiple data sources (product/packaging images, product descriptions, sensor data, geospatial data) to forecast package-related damages and optimize packaging decisions based on customer preference prediction Build causal inference model to capture the downstream impacts of different packaging designs and delivery experience Leverage generative AI technologies to develop scalable solutions for automated product compatibility and safety assessments (e.g., evaluating product shipping compatibility, safety requirements, and packaging configurations) Develop and implement computer vision solutions to automate packaging workflows and detect product/packaging defects in real-time operations Design and implement robotic control algorithms to optimize machine efficiency and meet diverse business objectives