Interdisciplinary Sys Engineer, GES NA Ops Engineering

Amazon • Bellevue, WA

1d

About The Position

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.
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.

Requirements

• 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

Nice To Haves

• 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 programs to drive results
• Master’s or PhD in mechanical, Industrial Engineering, Operations, or a related STEM field.
• Experience developing and supporting hardware/software systems across the product life cycle
• Background in robotics, mechatronics, or physical AI systems

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.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level