Amazon. com Services LLC
Technology
InterdisciplinarySysEngineer,GESNAOpsEngineering
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Interdisciplinary Sys Engineer, GES NA Ops Engineering at Amazon. com Services LLC. Skills: Computer vision, Automation systems, Edge computing, AI/ML deployment. Lead deployment of computer vision-enabled automation systems. Design integrated systems combining cameras, sensors, edge compute”
What You'll Achieve.
Enable real-time operational intelligence; Improve equipment performance; Optimize process flow; Translate capabilities into scalable systems; Translate capabilities into production-grade systems; Ensure seamless integration; Deliver best results for customers
Industry & Context.
Complex problem solving; Root cause analysis
Travel up to 30%, Up to three weeks consecutive travel, Travel including weekends
What They're Looking For.
Must Have
3+ years manufacturing equipment development, 5+ years hardware engineering, 3+ years systems engineering, Experience with video and image processing, Experience with computer vision, Experience with machine learning, Experience with Industrial control systems, Experience in complex problem solving, Experience working with and configuring sensors, Experience with edge compute devices, Hands-on experience with cameras, Hands-on experience with sensors, Hands-on experience with embedded/edge computing platforms, Hands-on experience with IIoT systems
Nice to Have
Master's degree in computer science, Master's degree in electrical engineering, Bachelor's degree in engineering, Bachelor's degree in technology, Bachelor's degree in computer science, Bachelor's degree in machine learning, Bachelor's degree in robotics, Bachelor's degree in operations research, Bachelor's degree in statistics, Bachelor's degree in mathematics, Experience with complex automated material handling equipment, Experience with packaging technologies, Experience building complex software systems, Experience deploying LLMs in production, 5+ years hardware design and validation, Master’s or PhD in mechanical engineering, Master’s or PhD in Industrial Engineering, Master’s or PhD in Operations, Master’s or PhD in related STEM field, Experience developing and supporting hardware/software systems, Background in robotics, Background in mechatronics, Background in physical AI systems
What You'll Do.
Lead deployment of computer vision-enabled automation systems
Design integrated systems combining cameras
Develop integrated systems enabling real-time monitoring
Develop integrated systems enabling decision-making
Bridge AI/ML models with physical systems
Enable reliable data capture
Enable processing pipelines
Enable low-latency inference on industrial equipment
Own hardware-software integration
Manage edge processing
Manage connectivity to systems
Productionize computer vision models
Ensure robustness of models
Ensure scalability of models
Ensure performance of models
Develop system validation strategies
Execute system validation strategies
Integrate with controls systems
Enable closed-loop automation
Enable actionable system responses
Design for reliability
Implement data filtering
Implement data masking
Implement fail-safe system behavior
Collaborate with vendors
Collaborate with internal teams
Prototype custom hardware
Prototype automation solutions
Scale custom hardware
Scale automation solutions
Drive standardization of architectures
Drive standardization of deployment patterns
Drive standardization of engineering best practices
Artifact specifications
Artifact strategic narratives
Set standard in organization for engineering excellence
How You'll Work.
Team & Collaboration
Partner with scientists; Partner with controls engineers; Partner with operations teams; Work closely with scientists; Collaborate with vendors; Collaborate with internal teams
Communication Scope
Communicate ideas effectively
Process & Methodology
End-to-end deployment, Program management
Full Job 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 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
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