AI/ML Engineer – Manufacturing Vision Inspection Systems

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

Overview Who we are Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As 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.

Who we’re looking for

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.

What you’ll be doing

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’sICS+,GALC, andTVIP 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.

What you bring

• 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.
• Willingness to work weekends, holidays, shutdowns, and multiple shifts as needed; up to 30% overtime.
• Ability to travel up to 30% (US, Canada, Mexico, other manufacturing sites, and Japan).
• Added bonus if you have Master's or advanced degree with a strong foundation in optical systems, computer vision, image processing, or AI automation.
• Research background in optical physics (specular reflection, deflectometry, multi-spectral imaging) applied to production-grade deep learning.
• 5+ years of software project management involving internal and external stakeholders.
• Experience integrating AI safety controls and optical fault-handling into PFMEAs, camera trigger reliability frameworks, and QCPs.
• Expertise in synthetic data generation (GANs, VAEs, NeRFs, Blender) and domain randomization.
• Experience with high-speed inline inspection and vision-based process control.
• Knowledge of IIoT data pipelines and messaging standards.

What we’ll bring

During your interview process, our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:

• A work environment built on teamwork, flexibility, and respect.
• Professional growth and development programs to help advance your career, as well as tuition reimbursement.
• Team Member Vehicle Purchase Discount.
• Toyota Team Member Lease Vehicle Program (if applicable).
• Comprehensive health care and wellness plans for your entire family.
• Toyota 401(k) Savings Plan featuring a company match, as well as an annual retirement contribution from Toyota regardless of whether you contribute (if applicable).
• Paid holidays and paid time off.
• Referral services related to prenatal services, adoption, childcare, schools, and more.
• Tax-Advantaged Accounts (Health Savings Account, Health Care FSA, Dependent Care FSA).
• Relocation assistance (if applicable).

Belonging at Toyota

Our success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star. Applicants for our positions are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law.

At Toyota, we don’t just have a vision, but a group of talented, dedicated people who work hard every day to turn that vision into reality. Our mission is to build a future where everyone has the freedom to move. We believe that nothing is impossible. We have big dreams and persevere through any obstacles. We work together to create the future of mobility and make the world a better place.

Career Possibilities

Toyota is a place for people who dream big and are determined to make those dreams a reality. We encourage innovation and look for people who will challenge the status quo in order to make the world a better place. We thrive on teamwork and collaboration and know diverse backgrounds, experiences and perspectives are not only the right thing for our people, they are a business imperative. Together, we’re empowered to forge our own paths — to be agile, curious and embrace a growth mindset and immerse ourselves in situations to gain new perspectives and to inspire bold, innovative ways of thinking and working. Our success as a company is directly tied to our team members’ success, and our collective ability to give back to society through an unwavering commitment to delight our customers and make people’s lives better. If you want to be part of the next-generation of innovations that help keep the world moving, then join us. And let’s start our impossible, together.