Control System Engineer

Title: Controls System Engineer Location: Georgetown, KY Duration: 12 months contract role with possible extensionLooking for experience in:Vision & Technology project.An ideal candidate should be experienced with machine learning and vision systems using PLC.5 years of experience in Machine Vision & Edge AI development.Proficiency in Python and C++.The primary responsibility of this role is:Model Development & Training SpeedDesign 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 DeploymentPackage 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 OptimizationOptimize 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 SystemsIntegrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST protocols.Align deployments with client’s ICS+, GALC, and TVIP architecture standards for plant-level connectivity and reliability.Data Strategy & Quality ControlLead 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 & SustainmentEnsure 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.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 doingDevelop 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 hardwareDevelopment of new technologies for PE and Manufacturing competitiveness improvementLead 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.Close collaboration between both internal and external groups across Client's department, automation teams & Plano divisions, to ensure quality and to integrate robust AI solutions into high-volume manufacturing environments.What you bringAbility to travel to Canada and Mexico; and to JapanExperience with project management including writing detailed scope of work, creating schedules, managing vendors/contractors, and providing regular status updates (Y/N – text follow up)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, TensorFlow).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 retrainingExperience 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 captureExperience balancing inspection accuracy with false positives vs flow-out risk in qualityDesired / PreferredMaster’s Degree in Engineering or Advanced Degree in related fieldsAcademic research experience in new technologyProject management work involving internal and external parties – 6 months or greaterExperience deploying equipment including establishing RJ, PFMEA, and quality control planExperience deploying automotive production equipmentExperience in Robotics to include operation, teaching, maintenance, and safetyExpertise 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.Key CompetenciesAbility to deliver production-ready AI solutions under strict timelines.Strong problem-solving and cross-functional collaboration skills.Commitment to quality, reliability, and continuous improvement in manufacturing environments