A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
Position Overview We are seeking an experienced Advanced Technology Engineer specializing in Machine Vision, Computer Vision, and Edge AI to develop and deploy next-generation inspection technologies within high-volume manufacturing environments. This position will focus on developing production-ready machine learning and computer vision solutions for automated quality inspection. The ideal candidate will have hands-on experience developing AI vision models, deploying them to edge hardware, and integrating vision systems with PLCs and industrial automation equipment. This role will also lead advanced technology projects from initial concept and testing through production implementation. Key Responsibilities Develop and deploy machine learning and computer vision models for defect detection, object detection, classification, and segmentation . Develop production-grade AI solutions for automated manufacturing inspection systems. Accelerate model development using synthetic data, active learning, data augmentation, and domain randomization . Optimize AI models for real-time inference on edge and embedded hardware, including NVIDIA Jetson and Intel accelerators . Integrate machine vision systems with PLCs, encoders, triggers, cameras, sensors, and industrial automation equipment . Support industrial communication protocols including OPC-UA, MQTT, and REST . Develop solutions using Python and C++ and machine learning frameworks such as PyTorch and TensorFlow . Deploy and manage applications using Docker, Kubernetes, ONNX Runtime, and TensorRT . Establish model version control, monitoring, rollback, and retraining processes. Monitor inspection accuracy, latency, model drift, false positives, and false negatives. Lead data collection, image labeling, validation, and model-quality activities. Optimize vision systems for changing lighting, optics, surface conditions, and production speeds. Support calibration and Measurement System Analysis (MSA) activities. Troubleshoot vision and inspection failures and perform root-cause analysis. Lead advanced technology projects from concept through manufacturing launch. Develop project schedules, scopes of work, milestones, punch lists, and status reports. Evaluate new technologies through manufacturing trials and develop business cases for implementation. Coordinate with manufacturing, engineering, automation, IT, vendors, and other technical teams. Support technology deployments at manufacturing facilities throughout North America. Required Qualifications Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Science, Information Technology , or a related technical field. 5+ years of experience with industrial machine vision, computer vision, and/or Edge AI deployment. Strong programming experience with Python and C++ . Experience with machine learning frameworks such as PyTorch or TensorFlow . Hands-on experience developing computer vision applications involving: Object detection Defect detection Classification Semantic or instance segmentation Experience integrating machine vision systems with PLC-controlled manufacturing equipment . Knowledge of industrial communication technologies such as OPC-UA and MQTT . Experience with industrial cameras, lighting, optics, and trigger-based image acquisition. Experience deploying AI/ML models to edge or embedded hardware. Familiarity with NVIDIA Jetson, Tensor
RT, ONNX
Runtime , or similar technologies. Experience with Docker and containerized software deployment. Familiarity with Kubernetes or similar orchestration technologies. Experience managing the complete machine learning lifecycle, including data collection, labeling, validation, deployment, monitoring, and retraining. Experience balancing inspection accuracy, false-positive rates, and quality flow-out risk. Ability to manage technical projects involving internal teams, vendors, and contractors. Ability to travel throughout North America, including Canada and Mexico , with potential international travel to Japan . Preferred Qualifications Master's degree in Engineering, Computer Science, AI/ML, or another related technical discipline. Experience developing AI or machine vision solutions within automotive or high-volume manufacturing . Experience with high-speed inline automated inspection systems. Experience with synthetic data generation , including GANs, VAEs, NeRFs, Blender, or domain randomization. Knowledge of IIoT architectures and industrial data pipelines. Experience with robotics, including operation, programming/teaching, maintenance, and safety. Experience deploying manufacturing equipment from development through production launch. Knowledge of PFMEA, quality control plans, MSA, and manufacturing quality systems . Academic or applied research experience involving emerging technologies. Ideal Candidate The ideal candidate combines AI/software development expertise with hands-on manufacturing automation experience . They understand how to build a computer vision model, optimize and deploy it to edge hardware, and integrate the solution with PLCs and production equipment. Candidates with experience implementing AI-driven automated inspection systems in automotive, battery, electronics, semiconductor, medical device, or other high-volume manufacturing environments are especially well suited for this opportunity.
