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

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Field Applications Engineer (FAE) – Manufacturing (Machine Vision & AI/ML) based in the United States.

This is a hands-on engineering role focused on deploying and optimizing machine vision and AI/ML solutions in real-world manufacturing environments.
You will work directly with engineering, operations, and quality teams on factory floors to solve complex inspection, automation, and process challenges.
The role combines computer vision, AI/ML, industrial automation, system integration, troubleshooting, and customer enablement.
You will help deploy production-ready vision systems involving cameras, optics, lighting, edge devices, and intelligent inspection models.
Your work will directly support improvements in product quality, throughput, yield, first-pass quality, and overall equipment effectiveness.
The position requires close collaboration with sales, deep-learning, product, and engineering teams to deliver effective customer solutions and continuous improvements.
This opportunity is well suited to a technically strong, customer-focused engineer who thrives in fast-paced production environments and is comfortable traveling 50% or more.

Accountabilities:

As a Field Applications Engineer, you will own hands-on deployment, integration, optimization, troubleshooting, and customer enablement activities while helping translate manufacturing challenges into scalable machine vision and AI-driven solutions.

• Work closely with sales and deep-learning teams to troubleshoot customer challenges, support deployments, and expand solution adoption.
• Travel 50% or more to customer manufacturing facilities for system installation, commissioning, troubleshooting, and ongoing support.
• Deploy and configure vision systems, including cameras, optics, lighting, and edge devices, within production environments.
• Diagnose and resolve electrical, mechanical, and software issues while working under real-time production constraints.
• Help minimize production downtime through rapid and effective issue resolution.
• Design and optimize machine vision solutions for inspection, defect detection, measurement, and guidance applications.
• Deploy and validate AI/ML models for real-world applications such as classification, object detection, and segmentation.
• Collect, label, organize, and manage image datasets to improve model performance.
• Tune models and systems for accuracy, latency, robustness, and consistent performance under variable factory conditions.
• Bridge the gap between data science models and reliable, production-ready inspection systems.
• Integrate solutions with PLCs, HMIs, robotics, and existing industrial automation systems.
• Support connectivity with MES, SCADA, and plant network infrastructure.
• Optimize system performance to improve throughput, yield, and first-pass quality.
• Execute proof-of-concepts, pilot programs, and full production deployments.
• Train operators, engineers, and quality teams on system operation, troubleshooting, and best practices.
• Develop documentation, standard operating procedures, and troubleshooting guides to support long-term adoption.
• Act as a trusted technical advisor to manufacturing, quality, and operations stakeholders.
• Translate production and inspection challenges into practical and scalable technical solutions.
• Provide structured feedback to product and engineering teams to improve system performance and usability.
• Contribute to successful production deployments, system uptime, model performance, defect reduction, scrap reduction, throughput improvements, OEE improvements, and customer satisfaction.

Requirements

The role requires a combination of engineering fundamentals, hands-on machine vision experience, industrial troubleshooting capabilities, and strong customer-facing communication skills.

• Bachelor’s degree in Engineering, Computer Science, or a related technical field.
• 3–8+ years of experience in manufacturing, industrial automation, field engineering, or a closely related area.
• Hands-on experience with machine vision systems and image formation in industrial environments.
• Strong troubleshooting capabilities across hardware and software systems.
• Ability and willingness to travel frequently, with 50% or more travel required.
• Experience designing or deploying computer vision solutions in produ…