Manufacturing Innovation Advanced Technology Engineer

We are seeking a highly skilled Manufacturing Innovation Advanced Technology Engineer to join our dynamic engineering team for a Major Automotive Client!

What makes our team stand out? Several things, but one of the most important things is that we offer AMAZING benefits!
We pay 100% for your medical, dental and vision benefit premiums. We also offer 17 PTO days, 8 Paid holidays, 401K match, and Paid OT.

The primary responsibility of this role is:

Reporting to the Manufacturing Innovation Manager, the person in this role will support the Production Engineering Division and SOAR Group’s objective to improve manufacturing competitiveness.

What you’ll be doing
:

• Experience balancing inspection accuracy with false positives vs flow-out risk in quality
• Design and implement computer vision models for defect detection, segmentation, and classification.
• Accelerate training cycles using synthetic data, active learning, and domain randomization to cover rare defects and specification variance.
• 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, drift, and false-positive/false-negative metrics.
• Edge Optimization
• Optimize inference for edge and embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) to meet strict real-time latency requirements for moving-line inspection.
• Ensure consistent performance under varying lighting, optics, and surface conditions.
• Integration with Manufacturing Systems
• Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST protocols.
• Align deployments with IC…?
• Data Strategy & Quality Control
• Lead data collection campaigns, manage annotation workflows, and establish quality gates for model validation.
• Utilize synthetic data pipelines and augmentation techniques to improve model robustness and reduce training time.
• Reliability & Sustainment
• Ensure uptime and availability targets are met 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 across manufacturing lines.
• Accelerating model development and training using advanced techniques such as synthetic data generation, ensuring high accuracy and generalization, and delivering containerized software optimized for edge hardware
• Development of new technologies for Manufacturing competitiveness improvement
• Lead and manage projects from concept to launch for new technology first introduction to manufacturing including creating schedules, establishing punch lists, and meeting established due dates and milestones.
• Search for innovative solutions, test them in a manufacturing setting, and develop business case justification to gain approval to purchase if trials prove successful.

Required Skills/

Experience:

• Ability to travel to all North American Manufacturing Centers (NAMC’s)-- including Canada and Mexico; and to Japan
• Experience with project management including writing detailed scope of work, creating schedules, managing vendors/contractors, and providing regular status updates
• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Information Technology or related field.
• 5 years of experience in industrial machine vision and edge AI deployment.
• Proficiency in Python and C++ with strong knowledge of ML frameworks (PyTorch, Tensor Flow).
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with ONNX Runtime, TensorRT, and optimization for embedded hardware.
• Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT).
• Experience managing the full model lifecycle: data collection, labeling, validation, rollout, monitoring, and retraining
• Experience in areas such as object detection, classification, segmentation and familiarity with mainstream object detection and semantic/instance segmentation models.
• Familiarity…