Interdisciplinary Sys Engineer, GES NA Ops Engineering

Computer Vision & Automation Engineer

Amazon is seeking an innovative, systems-oriented Computer Vision & Automation Engineer to help design and deploy next-generation intelligent automation solutions across global fulfillment networks. This role focuses on integrating computer vision, edge computing, and physical automation systems to enable real-time operational intelligence, improve equipment performance, and optimize process flow. The ideal candidate is a hands-on interdisciplinary engineer with expertise spanning hardware systems, embedded/edge computing, and automation environments, capable of bridging the gap between science (AI/ML models) and real-world deployment in industrial settings.

As a Computer Vision & Automation Engineer, you will partner closely with scientists, controls engineers, and operations teams to translate computer vision and AI capabilities into scalable, production-grade systems. You will lead the development and deployment of sensor-driven automation solutions, ensuring seamless integration across hardware, software, and control layers.

Key job responsibilities:

• Lead end-to-end deployment of computer vision-enabled automation systems across material handling environments, from concept through production rollout
• Design and develop integrated systems combining cameras, sensors, edge compute devices, and control interfaces to enable real-time monitoring and decision-making
• Bridge AI/ML models with physical systems by enabling reliable data capture, processing pipelines, and low-latency inference on industrial equipment
• Own hardware-software integration, including device selection, network configuration, edge processing, and connectivity to cloud or on-prem systems
• Work closely with scientists to productionize computer vision models, ensuring robustness, scalability, and performance in live operational environments
• Develop and execute system validation strategies including test plans, field trials, and performance benchmarking under real-world conditions
• Integrate with controls systems (e.g., PLCs, industrial protocols) to enable closed-loop automation and actionable system responses
• Design for safety, privacy, and reliability, including implementation of safeguards such as data filtering, masking, and fail-safe system behavior
• Collaborate with vendors and internal teams to prototype and scale custom hardware and automation solutions
• Drive standardization of architectures, deployment patterns, and engineering best practices for intelligent automation systems
• Artifact (research, schematics, specifications, prototypes, 3D Models, analysis, test plans, strategic narratives, etc.) and set the standard in organization for engineering excellence.
• Able to communicate ideas effectively to achieve the right outcome for team and customer. Seek diverse perspectives, listen to feedback, and are willing to change direction if it creates a better outcome. Harmonize discordant views and lead the resolution of contentious issues (build consensus).
• Travel up to 30% throughout North America, which can vary up to three weeks consecutive travel including weekends.

About the team

The Science & Advance Concepts (SAC) Team is responsible for optimizing material handling operations, enhancing automation, and driving innovation through Simulation/Emulation, Data Integrity/Analysis, and Pilot Development for existing first and middle mile buildings.