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Posted Apr 2, 2026

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

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Job Description: • 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