Manufacturing Innovation Advanced Technology Engineer

Georgetown, KY, US • Posted 4 hours ago • Updated 4 hours ago
Full Time
No Travel Required
On-site
Depends on Experience
Fitment

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Job Details

Skills

  • Machine Vision
  • Edge AI
  • Computer Vision
  • Python
  • C++
  • PyTorch / TensorFlow
  • Docker / Kubernetes

Summary

Please Read Before Applying

  • 5+ years in industrial machine vision and edge AI deployment
  • Proficiency in Python and C++ with ML frameworks (PyTorch, TensorFlow)
  • Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT)
  • Hands-on Docker containerization and Kubernetes orchestration
  • Onsite in Georgetown, KY; able to travel internationally as needed

About the Role

A leading automotive manufacturer’s Manufacturing Innovation / Advanced Technology group is seeking an Advanced Technology Engineer to develop and deploy production-grade machine learning and computer vision models for industrial inspection across high-volume manufacturing lines. You will accelerate model development with synthetic data, deliver containerized software optimized for edge hardware, and integrate robust AI solutions into manufacturing systems to improve competitiveness.

Responsibilities

  • Design and implement computer vision models for defect detection, segmentation, and classification
  • Accelerate training cycles using synthetic data, active learning, and domain randomization
  • Package models/services with Docker and manage deployments through Kubernetes or equivalent orchestration
  • Implement version control, rollback, and observability for latency, drift, and false-positive/negative metrics
  • Optimize inference for edge/embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) for real-time 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
  • Align deployments with plant-level connectivity and reliability standards
  • Lead data collection campaigns, manage annotation workflows, and establish quality gates for validation
  • Ensure uptime via proactive monitoring, calibration (MSA), drift detection, and root cause analysis
  • Lead and manage projects from concept to launch (schedules, punch lists, milestones)
  • Collaborate across manufacturing centers, corporate technical/R&D centers, IT, and automation teams

Required Qualifications

  • Bachelor’s degree in EE, ME, Computer Science, IT, or a related field
  • 5 years of experience in industrial machine vision and edge AI deployment
  • Python and C++ with strong knowledge of ML frameworks (PyTorch, TensorFlow)
  • Containerization (Docker) and orchestration (Kubernetes)
  • ONNX Runtime, TensorRT, and optimization for embedded hardware
  • Integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT)
  • Full model lifecycle: data collection, labeling, validation, rollout, monitoring, retraining
  • Object detection, classification, and segmentation (semantic/instance models)
  • Industrial cameras, lighting, optics, and trigger-based image capture
  • Balancing inspection accuracy with false positives vs. flow-out risk
  • Project management (scope, schedules, vendor/contractor management, status updates)
  • Ability to travel domestically and internationally (Canada, Mexico, Japan) as needed

Technical Skills

  • Python
  • C++
  • PyTorch
  • TensorFlow
  • Computer Vision (detection, segmentation, classification)
  • Edge AI (NVIDIA Jetson, Intel accelerators)
  • ONNX Runtime
  • TensorRT
  • Docker
  • Kubernetes
  • OPC-UA
  • MQTT
  • REST
  • PLC integration
  • Industrial cameras / optics
  • Synthetic data / domain randomization
  • MLOps

Preferred Qualifications

  • Master’s or advanced degree in engineering or a related field
  • Academic research experience in new technology
  • Project management involving internal and external parties (6+ months)
  • Equipment deployment including PFMEA and quality control plans
  • Deploying automotive production equipment
  • Robotics — operation, teaching, maintenance, and safety
  • Synthetic data generation (GANs, VAEs, NeRFs, Blender) and domain randomization
  • High-speed inline inspection and vision-based process control
  • IIoT data pipelines and messaging standards
  • Calibration, measurement system analysis (MSA), and quality-critical inspection

Must-Have Skills

  • Machine Vision
  • Edge AI
  • Computer Vision
  • Python
  • C++
  • PyTorch / TensorFlow
  • Docker / Kubernetes
  • PLC Integration
  • OPC-UA / MQTT
  • MLOps

Monster Skills List

  • Machine Vision
  • Computer Vision
  • Edge AI
  • Deep Learning
  • Machine Learning
  • Python
  • C++
  • PyTorch
  • TensorFlow
  • ONNX
  • TensorRT
  • Object Detection
  • Image Segmentation
  • Classification
  • Defect Detection
  • Docker
  • Kubernetes
  • NVIDIA Jetson
  • MLOps
  • Model Deployment
  • OPC-UA
  • MQTT
  • REST API
  • PLC
  • Industrial Automation
  • Industrial Cameras
  • Synthetic Data
  • Domain Randomization
  • GANs
  • MSA
  • IIoT
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10319786
  • Position Id: 9048143
  • Posted 4 hours ago
Contact the job poster
LS

Laurie Spencer

Recruiter @ TECKNOMIC LLC
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