Ua System Jobs in Kentucky (NOW HIRING)

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• 5+ years in industrial machine vision and edge AI deployment
• Proficiency in Python and C++ with ML frameworks (PyTorch, TensorFlow)
• Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT)
• Hands-on Docker containerization and Kubernetes orchestration
• Onsite in Georgetown, KY; able to travel internationally as needed

About the Role

A leading automotive manufacturer’s Manufacturing Innovation / Advanced Technology group is seeking an Advanced Technology Engineer to develop and deploy production-grade machine learning and computer vision models for industrial inspection across high-volume manufacturing lines. You will accelerate model development with synthetic data, deliver containerized software optimized for edge hardware, and integrate robust AI solutions into manufacturing systems to improve competitiveness.

Responsibilities

• Design and implement computer vision models for defect detection, segmentation, and classification
• Accelerate training cycles using synthetic data, active learning, and domain randomization
• Package models/services with Docker and manage deployments through Kubernetes or equivalent orchestration
• Implement version control, rollback, and observability for latency, drift, and false-positive/negative metrics
• Optimize inference for edge/embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) for real-time 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
• Align deployments with plant-level connectivity and reliability standards
• Lead data collection campaigns, manage annotation workflows, and establish quality gates for validation
• Ensure uptime via proactive monitoring, calibration (MSA), drift detection, and root cause analysis
• Lead and manage projects from concept to launch (schedules, punch lists, milestones)
• Collaborate across manufacturing centers, corporate technical/R&D centers, IT, and automation teams

Required Qualifications

• Bachelor’s degree in EE, ME, Computer Science, IT, or a related field
• 5 years of experience in industrial machine vision and edge AI deployment
• Python and C++ with strong knowledge of ML frameworks (PyTorch, TensorFlow)
• Containerization (Docker) and orchestration (Kubernetes)
• ONNX Runtime, TensorRT, and optimization for embedded hardware
• Integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT)
• Full model lifecycle: data collection, labeling, validation, rollout, monitoring, retraining
• Object detection, classification, and segmentation (semantic/instance models)
• Industrial cameras, lighting, optics, and trigger-based image capture
• Balancing inspection accuracy with false positives vs. flow-out risk
• Project management (scope, schedules, vendor/contractor management, status updates)
• Ability to travel domestically and internationally (Canada, Mexico, Japan) as needed

Technical Skills

• Python
• C++
• PyTorch
• TensorFlow
• Computer Vision (detection, segmentation, classification)
• Edge AI (NVIDIA Jetson, Intel accelerators)
• ONNX Runtime
• TensorRT
• Docker
• Kubernetes
• OPC-UA
• MQTT
• REST
• PLC integration
• Industrial cameras / optics
• Synthetic data / domain randomization
• MLOps

Preferred Qualifications

• Master’s or advanced degree in engineering or a related field
• Academic research experience in new technology
• Project management involving internal and external parties (6+ months)
• Equipment deployment including PFMEA and quality control plans
• Deploying automotive production equipment
• Robotics — operation, teaching, maintenance, and safety
• Synthetic data generation (GANs, VAEs, NeRFs, Blender) and domain randomization
• High-speed inline inspection and vision-based process control
• IIoT data pipelines and messaging standards
• Calibration, measurement system analysis (MSA), and quality-critical inspection

Must-Have Skills

• Machine Vision
• Edge AI
• Computer Vision
• Python
• C++
• PyTorch / TensorFlow
• Docker / Kubernetes
• PLC Integration
• OPC-UA / MQTT
• MLOps

Monster Skills List

• Machine Vision
• Computer Vision
• Edge AI
• Deep Learning
• Machine Learning
• Python
• C++
• PyTorch
• TensorFlow
• ONNX
• TensorRT
• Object Detection
• Image Segmentation
• Classification
• Defect Detection
• Docker
• Kubernetes
• NVIDIA Jetson
• MLOps
• Model Deployment
• OPC-UA
• MQTT
• REST API
• PLC
• Industrial Automation
• Industrial Cameras
• Synthetic Data
• Domain Randomization
• GANs
• MSA
• IIoT