Robotics & Computer Vision Engineer, GES NA Ops Engineering

Amazon

Bellevue, WA

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JOB DETAILS

SKILLS

3D Modeling, Analysis Skills, Artificial Intelligence (AI), Automation, Automation Engineering, Automation Systems, Autonomous Driving Systems, Benchmarking, Best Practices, Cloud Computing, Communication Skills, Compression Algorithms, Computer Engineering, Computer Maintenance, Computer Science, Computer Systems, Computer Vision, Control Engineering, Control Systems, Data Analysis, Data Collection, Data Quality, Deep Learning, Electrical Engineering, Embedded Hardware, Embedded Systems, Engineering, Field Trials, GPU (Graphics Processing Unit), Hardware Administration, Hardware Design, Hardware Development, Hardware-Software Integration, Image Processing, Industrial Engineering, Machine Learning, Manufacturing, Manufacturing Equipment, Mathematics, Mechanical Engineering, Network Configuration Management, Operations Planning, Operations Research, Problem Solving Skills, Product Lifecycle, Production Systems, Programmable Logic Controller (PLC), Prototyping, Robotics, Schematics, Simulation, Software Administration, Statistics, Strategic Planning, System Integration (SI), System Validation, Systems Engineering, Test Strategy, Testing, Time Tracking, Video Processing, Willing to Travel, Wireless Communications

LOCATION

Bellevue, WA

POSTED

30+ days ago

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 advancing physical AI and autonomous systems, including SLAM-based navigation, localization, and autonomous decision-making in real-world environments The ideal candidate is a hands-on interdisciplinary engineer with expertise spanning hardware systems or 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 Robotics 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. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Bellevue - 129,200.00 - 174,800.00 USD annually

About the Company

Amazon

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

COMPANY SIZE

10,000 employees or more

INDUSTRY

Other/Not Classified

FOUNDED

1994

WEBSITE

http://Amazon.com/militaryroles

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