Quantum computing Jobs in Renton, WA

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 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.

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 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers.