AI​/ML Engineer - Manufacturing Vision Inspection Systems

Overview

Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like  one of the world's most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We're looking for talented team members who want to Dream. Do. Grow.

with us.

Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like  one of the world's most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We're looking for talented team members who want to Dream. Do. Grow.

with us.

Toyota does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future. You must have the right to work in the United States and not require Toyota support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, 'job flexibility benefits' [also known as I-140 or Adjustment of Status portability], etc.)

now or in the future. You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future.

Toyota's Manufacturing Innovation and Transformation Department is looking for a passionate and highly motivated Engineer. Reporting to the Manufacturing Innovation Manager, this role leads end-to-end engineering and deployment of next-generation automated quality inspection systems for Toyota's North American manufacturing facilities, supporting the Production Engineering Division and SOAR Group's goal of improving manufacturing competitiveness.

• Model Development & Training
• Design and implement computer vision models for defect detection, segmentation, and classification.
• Accelerate training cycles using synthetic data, active learning, and domain randomization, including for rare edge-case defects.
• Production Deployment & MLOps
• Package models with Docker and manage deployments via Kubernetes (K8s) or equivalent orchestration.
• Implement MLOps practices - version control, rollback strategies, and observability for latency, lighting drift, and false-positive/negative rates on production lines.
• Edge Optimization
• Optimize inference for edge/embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) to meet real-time latency requirements for moving-line inspection.
• Maintain consistent performance across varying lighting, optics, and surface conditions.
• Manufacturing System Integration
• Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST.
• Align deployments with Toyota's IC S+, GALC, and TVIP architecture standards for plant-level connectivity and reliability.
• Data Strategy & Quality Control
• Lead defect image collection campaigns, manage annotation workflows, and set quality gates for model validation.
• Use synthetic data pipelines and augmentation to improve robustness and reduce training time.
• Reliability & Sustainment
• Meet uptime/availability targets through proactive monitoring, calibration (MSA), and backup/restore processes.
• Implement drift detection, audit false negative risk, and conduct root cause analysis for inspection failures.
• Innovation & Collaboration
• Pioneer new deflectometry, reflection, and multi-camera imaging technologies to elevate vehicle surface quality control.
• Lead inspection booth software deployments from concept through SOP (Start of Production).
• Evaluate optical AI solutions through on-site plant trials, compiling data for North American rollout.
• Collaborate across NAMCs, Toyota Motor Corp (TMC), Toyota Technical Center (TTC), PE support shops, IT (One Tech), automation teams, and Enterprise AI divisions.

• 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…