Advanced Innovation Manufacturing Engineer, Contingent Worker

WillHire; Georgetown (KY); On-site; USD 69,000 - 94,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401K

Job summary

Magnit Direct Sourcing, on behalf of Toyota, seeks an Advanced Innovation Manufacturing Engineer for a 12-month contract in Georgetown, Kentucky. The role focuses on developing and deploying computer vision models for defect detection on manufacturing lines, with edge optimization for NVIDIA Jetson/Intel accelerators.

You will lead data collection and model validation, accelerate training with synthetic data, and integrate vision systems with PLCs and industrial protocols.

Qualifications

• Master’s degree in Engineering or related field.
• 2+ years of experience in industrial machine vision and edge AI deployment.
• Proficiency in Python and C++ with ML frameworks (PyTorch, TensorFlow).
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Experience with OPC-UA, MQTT and integrating vision systems with PLCs.

Responsibilities

• Develop and deploy production‑grade ML models for industrial vision inspection systems.
• Accelerate model development using synthetic data and domain randomization.
• Package models and services using Docker; manage deployments via Kubernetes or equivalents.
• Lead data collection, labeling, and quality gates for model validation.

Skills

Computer vision

Python

C++

Docker

Kubernetes

ONNX Runtime

TensorRT

OPC-UA

MQTT

Industrial cameras

Education

Master’s Degree in Engineering

Tools

Docker

Kubernetes

ONNX Runtime

TensorRT

Job description

Magnit Direct Sourcing on behalf of Toyota is currently hiring an Advanced Innovation Manufacturing Engineer for a temporary assignment in Georgetown, Kentucky.

This is a 12-month contract. The pay range for this role is between $50.00- $68.00/Hr. Benefits: Medical, Dental, Vision, 401K.

Description

Model Development & Training Speed

• Design and implement computer vision models for defect detection, segmentation, and classification.
• Accelerate training cycles using synthetic data, active learning, and domain randomization to cover rare defects and specification variance.

Production Deployment

• Package models and services using Docker and manage deployments through Kubernetes or equivalent orchestration tools.
• Implement version control, rollback strategies, and observability for latency, drift, and false-positive/false-negative metrics.

Edge Optimization

• Optimize inference for edge and embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) to meet strict real-time latency requirements for moving-line inspection.
• Ensure consistent performance under varying lighting, optics, and surface conditions.

Integration with Manufacturing Systems

• Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST protocols.
• Align deployments with IC S+, GALC, and TVIP architecture standards for plant-level connectivity and reliability.

Data Strategy & Quality Control

• Lead data collection campaigns, manage annotation workflows, and establish quality gates for model validation.
• Utilize synthetic data pipelines and augmentation techniques to improve model robustness and reduce training time.

Reliability & Sustainment

• Ensure uptime and availability targets are met through proactive monitoring, calibration (MSA), and backup/restore processes.
• Implement drift detection, audit false-out risks, and perform root cause analysis for inspection failures.

Reporting to the Manufacturing InnovationManager, the person in this role will support the Production Engineering objectiveto improve manufacturing competitiveness.

Key Responsibilities

• Develop and deploy production-grade machine learning models for industrial vision inspection systems across manufacturing lines.
• Accelerating model development and training using advanced techniques such as synthetic data generation, ensuring high accuracy and generalization, and delivering containerized software optimized for edge hardware
• Development of new technologies for PE and Manufacturing competitiveness improvement
• Lead and manage projects from concept to launch for new technology first introduction to manufacturing including creating schedules, establishing punch lists, and meeting established due dates and milestones.
• Search for innovative solutions, test them in a manufacturing setting, and develop business case justification to gain approval to purchase if trials prove successful.
• Close collaboration between both internal and external groupsto ensurequalityandto integrate robust AI solutions into high-volume manufacturing environments.

Qualifications

• Ability to travel to all North American Manufacturing Centers along with Canada, MexicoandJapan
• Experience with project management including writing detailed scope of work, creating schedules, managing vendors/contractors, and providing regular status updates (Y/N – text follow up)
• Bachelor’sdegree inElectrical Engineering, Mechanical Engineering,Computer Science, InformationTechnologyor related field.
• 2+( 5preferred)years of experience in industrial machine vision and edge AI deployment.
• Proficiencyin Python and C++ with strong knowledge of ML frameworks (PyTorch, TensorFlow).
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with ONNX Runtime,TensorRT, and optimization for embedded hardware.
• Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT).
• Experience managing the full model lifecycle: data collection, labeling, validation, rollout, monitoring, and retraining
• Experience in areas such as object detection, classification, segmentation and familiarity with mainstream object detection and semantic/instance segmentation models
• Familiarity with industrial cameras, lighting, and optics, including trigger-based image capture
• Experience balancing inspection accuracy with false positives vs flow-out risk in quality-critical applications

Education/Experience

• Master’s Degree in Engineering or AdvancedDegreein related fields
• 2-5 years of experience.
• Academic research experience innew technology
• Project management work involving internal and external parties – 6 monthsor greater
• Experience deploying equipment includingestablishingRJ,PFMEA, andqualitycontrol plan
• Experience deployingautomotive production equipment
• Experience in Robotics to include operation, teaching,maintenance,and safety
• Expertise insynthetic data generation techniques (GANs, VAEs,NeRFs, Blender) and domain randomization for model generalization.
• Experience with high-speed inline inspection systems and vision-based process control.
• Knowledge ofIIoTdata pipelines and messaging standards.
• Strong understanding of calibration, measurement system analysis (MSA), and quality-critical inspection requirements.

Added Bonus

• Ability to deliver production-ready AI solutions under strict timelines.
• Strong problem-solving and cross-functional collaboration skills.
• Commitment to quality, reliability, and continuous improvement in manufacturing environments

Magnit Direct Source 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 Magnit Direct Source 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 Magnit Direct Source to assist with immigration support or sponsorship now or in the future.

Magnit is an equal opportunity employer, and all applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.

Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation.