Interdisciplinary Sys Engineer, GES NA Ops Engineering

Description

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 an 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 product ionize 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.

Basic Qualifications

- 3+ years of manufacturing equipment development experience, or Master's degree in computer science or electrical engineering

- 5+ years of hardware engineering experience

- 3+ years of systems engineering experience, or Bachelor's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

- Experience with video and image processing and compression algorithms and standards, computer vision and/or machine learning

- Experience with Industrial control systems, both hardware and software

- Experience in complex problem solving, and working in a tight schedule environment

- Experience working with and configuring sensors (vision, depth, etc.) and edge compute devices in industrial environments.

- Hands-on experience with cameras, sensors, embedded/edge computing platforms, or IIoT systems

Preferred Qualifications

- Experience with complex automated material handling equipment, packaging technologies, and systems and high-speed manufacturing

- Experience in creating products and services with hardware and software integrated

- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

- Experience in embedded wireless systems, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

- 5+ years of hardware design and validation of components, subsystems and systems experience

- Experience owning end-to-end…