Manufacturing Innovation Advanced Technology Engineer

Advanced Technology Engineer – Vision & Edge AI

The Advanced Technology Engineer will develop and deploy AI-powered machine vision systems for defect detection and quality inspection in high-volume manufacturing environments.

The primary focus of this role is building production-ready computer vision models, optimizing them for real-time edge hardware, and integrating them into manufacturing systems.

• Design and implement computer vision models for defect detection, segmentation, and classification.
• Accelerate training cycles using synthetic data, active learning, and domain randomization to address rare defects and specification variance.

• Package models and services using Docker and manage deployments through Kubernetes or equivalent orchestration tools.
• Implement version control, rollback strategies, and monitoring for latency, model drift, and false-positive/false-negative metrics.

• Optimize inference for edge and embedded hardware (e.g., NVIDIA Jetson, Client accelerators) to meet strict real-time latency requirements for moving-line inspection.
• Ensure consistent performance under varying lighting, optics, and surface conditions.

• Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST protocols.
• Align deployments with plant-level architecture and connectivity standards to ensure reliability and scalability.

• Lead data collection campaigns and manage annotation workflows.
• Establish quality gates for model validation.
• Utilize synthetic data pipelines and augmentation techniques to improve robustness and reduce training time.

• Ensure uptime and availability targets through proactive monitoring, calibration (MSA), and backup/restore processes.
• Implement drift detection, audit false-out risks, and perform root cause analysis for inspection failures.

• Develop and deploy production-grade machine learning models for industrial vision inspection systems.
• Accelerate model development using synthetic data and advanced AI techniques.
• Deliver containerized software optimized for edge hardware.
• Lead projects from concept through launch, including scheduling, milestone tracking, and cross-functional coordination.
• Evaluate new technologies in manufacturing environments and build business cases for adoption.
• Collaborate with internal engineering, IT, automation, and production teams to integrate robust AI solutions into high-volume manufacturing.

• Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Science, IT, or related field.
• 5+ years of experience in industrial machine vision and edge AI deployment.
• Strong proficiency in Python and C++.
• Experience with ML frameworks (PyTorch, Tensor Flow).
• Hands-on experience with Docker and Kubernetes.
• Familiarity with ONNX Runtime, TensorRT, and embedded optimization.
• Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT).
• Experience managing the full AI lifecycle: data collection, labeling, validation, rollout, monitoring, and retraining.
• Knowledge of object detection, classification, and segmentation models.
• Experience with industrial cameras, lighting, and trigger-based image capture.

• Master's degree or advanced engineering degree.
• Experience deploying automotive or high-volume production equipment.
• Robotics experience (operation, teaching, maintenance, safety).
• Expertise in synthetic data generation (GANs, VAEs, NeRFs, Blender) and domain randomization.
• Experience with high-speed inline inspection systems and IIoT data pipelines.
• Strong understanding of calibration, MSA, PFMEA, and quality-critical inspection requirements.

• Ability to deliver production-ready AI solutions under strict timelines.
• Strong cross-functional collaboration and project leadership skills.
• Commitment to quality, reliability, and continuous improvement in manufacturing environments.