Director Operational Technology Engineer Jobs in Kentucky

Job Overview:

Pay Range $60hr - $65hr

Requirement/Must Have:

• Proficiency in Python and C++.
• 5+ years of experience in industrial machine vision and edge AI deployment.
• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Information Technology or related field.
• Experience with project management including writing detailed scope of work, creating schedules, managing vendors/contractors, and providing regular status updates.
• 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 with industrial cameras, lighting, and optics, including trigger-based image capture.

Responsibilities:

• 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.
• 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.
• 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 organizational architecture standards for plant-level connectivity and reliability.
• 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.
• 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.

Nice to Have:

• Master’s Degree in Engineering or Advanced Degree in related fields.
• Academic research experience in new technology.
• Project management work involving internal and external parties – 6 months or greater.
• Experience deploying equipment including establishing RJ, PFMEA, and quality control plan.
• Experience deploying automotive production equipment.
• Experience in Robotics to include operation, teaching, maintenance, and safety.
• Expertise in synthetic data generation techniques (GANs, VAEs, NeRFs, Blender) and domain randomization for model generalization.
• Experience with high-speed inline inspection systems and vision-based process control.
• Knowledge of IIoT data pipelines and messaging standards.
• Strong understanding of calibration, measurement system analysis (MSA), and quality-critical inspection requirements.

Skills:

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

• Medical, Dental, and Vision Insurance
• 401(k) Retirement Plan
• Health Savings Account (HSA)
• Disability Insurance (Short-Term and Long-Term)
• Life and AD&D Insurance
• Paid Sick Leave (where required by applicable state or local law)
• Supplemental Insurance Plans
• Identity Theft Protection
• Pet Insurance
• Employee Wellness Programs
• Employee Assistance Program (EAP)
• Career Growth and Professional Development Opportunities