Field Applications Engineer – Manufacturing, Machine Vision, AI/ML

Role Overview

• On-Site Deployment & Support
• 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
• Machine Vision & AI/ML Implementation
• 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
• System Integration & Optimization
• 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
• Customer Training & Enablement
• 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
• Customer Collaboration
• 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
• Success Metrics
• 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

Requirements

• 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
• Preferred 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 improvement methodologies
• Bonus points if... Strong hands-on expertise in machine vision and AI-driven inspection systems
• Ability to troubleshoot and optimize systems in high-pressure production environments
• Systems thinking across hardware, software, and data pipelines
• Clear communication with operators, engineers, and executives
• Adaptability in fast-paced, variable manufacturing conditions
• Located near a major airport for necessary travel

Benefits

• Competitive pay and equity
• The chance to constantly work on stimulating intellectual challenges
• Gym membership reimbursement
• Medical, dental, and vision insurance with 100% paid premiums
• A budget for whatever hardware or software will make you most effective
• Regular tech talks to discuss the latest advances in CV, DL and software engineering