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Robotics & Computer Vision Engineer, GES NA Ops Engineering

Job in Factoria, King County, Washington, USA
Listing for: Amazon
Full Time position
Listed on 2026-07-08
Job specializations:
  • Engineering
    AI Engineer (Applied/Software), Robotics, Systems Engineer
Salary/Wage Range or Industry Benchmark: 129200 - 174800 USD Yearly USD 129200.00 174800.00 YEAR
Job Description & How to Apply Below
Location: Factoria

Job :  |  Services LLC

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.

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
  • Communicate ideas effectively to achieve the right outcome for team and customer. Seek diverse perspectives, listen to feedback, and be 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,…
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