Industrial Vision AI Engineer — Real-Time Defect Detection

TNA Toyota Motor Engineering & Manufacturing North America, Inc. Company; United States; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health care and wellness plans

401(k) Savings Plan with company match

Relocation assistance

Paid holidays and paid time off

Vehicle Purchase Discount

Job summary

Toyota Motor Engineering & Manufacturing North America, Inc. Company seeks an Engineer to lead end-to-end development and deployment of vision-based quality inspection systems across North American plants. You will design models for defect detection, optimize for edge hardware, and integrate with plant networks.

The role requires strong experience in machine vision, Docker/Kubernetes, and AI model lifecycle management, with travel up to 30% across NA sites and partner facilities.

Qualifications

• Bachelor's degree or higher in Engineering, Computer Science, IT, or related field.
• 2+ years in industrial machine vision and edge AI deployment.
• 3+ years of AI/ML experience with camera-based vision systems.
• Experience managing the full model lifecycle: data collection, labeling, validation, rollout, monitoring, retraining.
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Knowledge of ONNX Runtime, TensorRT, and embedded hardware optimization.

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 with Docker and manage deployments via Kubernetes or equivalent orchestration.
• Implement MLOps practices — version control, rollback strategies, and observability for latency, lighting drift, and false-positive/negative rates on production lines.
• Optimize inference for edge/embedded hardware to meet real-time latency requirements.
• Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST.
• Lead defect image collection campaigns, manage annotation workflows, and set quality gates for model validation.

Skills

Machine vision

Edge AI

Docker

Kubernetes

Travel up to 30%

Education

Bachelor's degree or higher in Engineering/CS/IT

Master's degree in related field

Tools

NVIDIA Jetson

ONNX Runtime

TensorRT

Docker

Kubernetes

OPC-UA

Job description

Toyota Motor Engineering & Manufacturing North America, Inc. Company seeks an Engineer to lead end-to-end development and deployment of vision-based quality inspection systems across North American plants. You will design models for defect detection, optimize for edge hardware, and integrate with plant networks.

The role requires strong experience in machine vision, Docker/Kubernetes, and AI model lifecycle management, with travel up to 30% across NA sites and partner facilities.