Field Applications Engineer; FAE – Manufacturing; Machine Vision & AI​/ML

Field Applications Engineer (FAE) – Manufacturing (Machine Vision & AI/ML)

Matroid is a full-service computer vision company that has developed an end-to-end platform allowing enterprise customers to rapidly train and
deploy automated visual inspection on imagery including EO, IR, X-Ray, CT, OCT, and others.

Founded in 2016 by a Stanford professor, Matroid has a broad and rapidly growing set of customers in manufacturing, industrial IoT, government and security.

We are seeking a hands‑on, customer‑focused Field Applications Engineer (FAE) to support the deployment and optimization of machine vision and AI‑driven solutions in manufacturing environments. This role is highly technical and field‑based, requiring frequent travel to customer facilities (50%+) to ensure successful implementation, integration, and performance in real‑world production settings. You will work directly on factory floors with engineering, operations, and quality teams to solve complex inspection, automation, and process challenges—leveraging computer vision and AI/ML to improve quality, throughput, and efficiency.

• Working directly with the sales and deep‑learning teams to most effectively problem solve, support, and expand Matroid by users.
• Travel to customer manufacturing facilities (50%+ travel required) for system installation, commissioning, and support
• Deploy and configure vision systems (cameras, optics, lighting, edge devices) in production environments
• Troubleshoot electrical, mechanical, and software issues under real‑time production constraints
• Ensure minimal downtime and rapid resolution of issues

• Design and optimize vision solutions for inspection, defect detection, measurement, and guidance
• Deploy and validate AI/ML models for real‑world use (e.g., classification, object detection, segmentation)
• Collect, label, and manage image datasets to improve model performance
• Tune models and systems for accuracy, latency, and robustness in variable factory conditions
• Bridge the gap between data science models and production‑ready systems

• Integrate solutions with PLCs, HMIs, robotics, and existing automation systems
• Support connectivity with MES, SCADA, and plant network infrastructure
• Optimize system performance for throughput, yield, and first‑pass quality
• Execute proof‑of‑concepts (POCs), pilot programs, and full production rollouts

• Train operators, engineers, and quality teams on system operation and best practices
• Develop documentation, SOPs, and troubleshooting guides
• Support long‑term adoption and continuous improvement initiatives
• Act as a trusted technical advisor to manufacturing, quality, and operations teams
• Translate production and inspection challenges into scalable technical solutions
• Provide structured feedback to product and engineering teams to improve system performance and usability

• Successful deployment and uptime of vision/AI systems in production
• Model performance (accuracy, false positive/negative rates) in real‑world conditions
• Reduction in defects, scrap, or manual inspection
• Improvements in throughput and overall equipment effectiveness (OEE)
• Customer satisfaction and repeat engagements

• Bachelor’s degree in Engineering, Computer Science, or related technical field
• 3–8+ years of experience in manufacturing, industrial automation, or field engineering
• Hands‑on experience with machine vision systems (image formation) in industrial environments
• Strong troubleshooting skills across hardware and software systems
• Ability to travel frequently (50% or more), including time on factory floors

• Experience with:
  • Computer vision frameworks (e.g., OpenCV, deep learning‑based tools)
  • AI/ML model deployment in production environments
  • PLCs (Allen‑Bradley, Siemens) and industrial automation systems
  • Industrial networks (Ethernet/IP, PROFINET, Modbus)
  • Cameras, lenses, lighting, and image acquisition systems
• Familiarity with:
  • Data annotation tools and dataset management
  • Edge computing or GPU‑based inference systems
  • Lean manufacturing, Six Sigma, or continuous…