Applied Scientist II, Computational Modeling, OMHS SCS
Job ID: 10529078 | Amazon.com Services LLC - A57
Are you excited about applying machine learning and applied mathematics to real-world systems at massive scale? As an Applied Scientist on this newly formed team, you will collaborate closely with scientists and engineers to bring research into production across a broad portfolio of problems — from computer vision perception platforms to building-wide optimization and orchestration. You will frame ambiguous business problems as tractable scientific challenges and implement novel machine learning (ML) systems, first-principles models, embedded systems prototypes, and performance optimizations in both prototype and production environments. This is a ground-floor opportunity to shape the scientific direction of a new organization, where your contributions will directly influence how Amazon's fulfillment network operates and evolves.
Design, develop, and deploy ML and scientific solutions spanning classical machine learning, statistical modeling, computer vision, optimization,



and physics-informed modeling in production environments.
Rapidly ramp on unfamiliar problem domains, frame ambiguous business problems as tractable scientific challenges, and prototype solutions end to end.
Author or co-author research findings for internal or external peer-reviewed venues, and provide peer feedback on research procedures and results across teams.
Prototype and evaluate sensing hardware and lightweight, edge-deployable models that run on commodity compute under real-world constraints.
Collaborate across multiple science and engineering teams to integrate your solutions into deployment architecture, mentoring less experienced scientists along the way.
You might start your morning reviewing experiment results from an overnight model training run, then shift into a design discussion with engineers on how to deploy a new computer vision model to edge hardware in a fulfillment cente

📌 Applied Scientist II, Computational Modeling, OMHS SCS (Italia)
🏢 Amazon
📍 Italia