Job Summary

The Hardware Engineer will own the hardware backbone of computer-vision manufacturing products, with primary near-term focus on vision inspection products and support for additional product hardware needs as platforms mature. The role will be responsible for cameras, edge compute devices, power supply mechanisms, and network infrastructure deployed across manufacturing plants. Responsibilities span hardware specification, sourcing, testing, safety and regulatory certification, deployment, fleet management, and sustaining support. The engineer will collaborate closely with applied AI, software engineering, product management, manufacturing, IT, and plant deployment teams to translate product and algorithm requirements into reliable hardware solutions.

Key Responsibilities
• Own end-to-end camera specifications for vision inspection stations, including resolution selection, lens selection, field-of-view and working-distance calculations, and lighting requirements.
• Evaluate and qualify camera vendors and industrial vision hardware models against plant-floor environmental conditions such as vibration, dust, temperature, and wash-down requirements.
• Define and maintain hardware bill-of-materials (BOM) standards for repeatable and scalable station builds.
• Specify, test, and validate edge compute devices, including industrial PCs and edge systems supporting vision inference and messaging.
• Support MQTT broker/client architecture and communication between cameras and plant control systems.
• Own network architecture decisions for vision hardware, including wired plant Ethernet connectivity, camera-to-switch connectivity, GigE configuration, and production-load validation.
• Perform jumbo-frame and packet-loss testing during image capture and transfer.
• Partner with software engineering on PLC integration requirements, including pass/fail signal handoff, to ensure hardware and controls interfaces are properly specified and tested.
• Manage edge device procurement and lifecycle activities, including requisitioning, provisioning, refresh cycles, and coordination with program and IT stakeholders.
• Lead hardware validation and test protocols for new camera and edge-device deployments before plant rollout.
• Perform environmental, network, and integration testing for hardware deployments.
• Own UL/cUL certification requirements and compliance documentation for fielded hardware.
• Coordinate safety and compliance activities with applicable EHS and safety stakeholders.
• Support Cyber Security, OGC, and Corporate Ergonomics review and sign-off processes required for new hardware deployments.
• Establish and maintain fleet management practices for deployed camera and edge hardware, including inventory, firmware and health monitoring, warranty tracking, and end-of-life replacement planning.
• Partner with software and cloud teams on image storage and retention considerations, including cloud-based image storage and data lifecycle requirements.
• Serve as the primary hardware escalation point for plant-floor issues involving cameras, edge devices, or network connectivity.
• Drive root cause analysis and corrective actions for hardware-related issues.
• Provide hardware engineering support across vision product deployments and additional product lines as deployment scope grows.
• Collaborate with applied AI vision engineering and product management to translate product and algorithm requirements into hardware specifications.
• Develop and govern hardware standards and support continuous improvement initiatives.

Required Qualifications
• Bachelor's degree in Electrical Engineering, Computer Engineering, Mechatronics, or a related field, or equivalent practical experience.
• 5+ years of hands-on experience specifying, testing, or deploying industrial cameras, machine vision hardware, or edge compute devices.
• Working knowledge of industrial networking concepts, including Ethernet, GigE, network switches, jumbo frames, and packet-level troubleshooting.
• Familiarity with safety and regulatory certification processes, including UL/cUL, for electrical and electronic hardware.
• Experience with messaging and integration protocols used in industrial vision systems, including MQTT.
• Understanding of PLC interfacing concepts.
• Strong cross-functional communication skills with the ability to work effectively with software engineers, product managers, IT teams, and plant personnel.

Preferred Qualifications
• Direct experience with industrial PCs and NVIDIA products for AI applications.
• Experience supporting hardware fleets at scale across multiple manufacturing sites.
• Familiarity with cloud-based image storage and retention pipelines, including GCP, and their relationship to hardware warranty and data lifecycle policies.
• Manufacturing or automotive plant-floor experience.
• Experience developing and governing hardware standards.