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