Manufacturing Innovation Advanced Technology Engineer

Manufacturing Innovation Advanced Technology Engineer

Georgetown, Kentucky

On-Site | Contract Opportunity

$50–$55 per Hour

Position Highlights

• Full-time hours
• On-site position in Georgetown, KY
• Long-term contract opportunity
• PTO
• Paid holidays
• Competitive pay and benefits
• Benefits begin Day 1

Position Summary

We are seeking a highly skilled Manufacturing Innovation Advanced Technology Engineer to support the development and deployment of advanced AI and computer vision technologies within high-volume manufacturing environments.

This role will focus on developing production-grade machine learning models for industrial vision inspection systems, accelerating model training, optimizing AI solutions for edge hardware, and integrating vision systems with manufacturing equipment and industrial networks.

Reporting to the Manufacturing Innovation Manager, this position will support the Production Engineering Division and SOAR Group's efforts to improve manufacturing competitiveness through innovative technology solutions.

The ideal candidate will have strong experience in industrial machine vision, edge AI, machine learning, and manufacturing technology, along with the ability to take projects from concept through production launch.

Key Responsibilities

Model Development & Training

• 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
• Develop and deploy production-grade machine learning models for industrial vision inspection systems across manufacturing lines
• Utilize synthetic data pipelines and augmentation techniques to improve model robustness and reduce training time
• Manage the full model lifecycle, including data collection, labeling, validation, rollout, monitoring, and retraining

Production Deployment

• Package models and services using Docker and manage deployments through Kubernetes or equivalent orchestration tools
• Implement version control, rollback strategies, and observability for latency, model drift, and false-positive/false-negative metrics
• Deliver containerized software optimized for production and edge environments

Edge Optimization

• Optimize inference for edge and embedded hardware, including NVIDIA Jetson and Intel accelerators
• Ensure AI solutions meet strict real-time latency requirements for moving-line inspection
• Ensure consistent system performance under varying lighting, optics, and surface conditions
• Utilize technologies such as ONNX Runtime and TensorRT to optimize models for embedded hardware

Integration with Manufacturing Systems

• Integrate vision systems with PLCs, encoders, triggers, and industrial networks
• Utilize industrial communication protocols including OPC-UA, MQTT, and REST
• Align technology deployments with Toyota's ICS+, GALC, and TVIP architecture standards for plant-level connectivity and reliability
• Collaborate with automation, IT, engineering, and manufacturing teams to ensure robust integration of AI solutions

Data Strategy & Quality Control

• Lead data collection campaigns and manage annotation workflows
• Establish quality gates for model validation and production readiness
• Monitor inspection accuracy and balance false-positive rates against flow-out risk
• Implement drift detection and audit false-out risks
• Perform root cause analysis for inspection failures an