Software Development Engineer, OneMHS

We are seeking an exceptional Software Development Engineer to build and scale edge machine learning compute, equipment monitoring, and computer vision capabilities across our global fulfillment network. Our landscape is global and complex, spanning diverse software systems, industrial machines, and protocols. We continuously innovate on behalf of the customer by building custom hardware and software technology solutions. As a lead on this team, you will develop edge-based solutions where the cloud meets the real world in the heart of our fulfillment centers. Your work will span multiple layers of the stack from low-level embedded Linux control systems to cloud-based platforms that interface with and manage fleets of real-world devices. You will collaborate closely with an inter-disciplinary team and external partners to drive product definition, execution, and testing. Key job responsibilities * Evolve our internal ML experimentation platform to support edge deployment workflows across Amazon's warehouse network * Build and maintain edge services managing camera fleets at scale, including telemetry infrastructure and data pipelines for OEE analytics * Collaborate with cross-functional teams — hardware, operations, applied science — to ship new capabilities * Mentor junior engineers and help shape the team's engineering culture A day in the life On a typical day as an OneMHS SDE, you might: * Experiment with state-of-the-art Computer Vision models to enable new science capabilities * Unify and clarify conflicting OEE metrics, negotiating and investigating with partners * Debug why an ML inference pipeline is dropping frames on a specific edge device * Prototype a new telemetry dashboard to surface machine health across hundreds of sites * Review a teammate's PR for a new device provisioning workflow About the team We're the Science and Software team within OneMHS (Material Handling Systems). We're building the foundation for next-generation ML, computer vision, and AI applications for Amazon's material handling systems — combining expertise in distributed systems, industrial automation, cloud architecture, and machine learning to deliver solutions that impact millions of customers daily.