JOB SUMMARY
Agratas Vision System and Inspection Subject Matter Expert (SME) should be a technical authority responsible for supporting our Global Manufacturing Engineering team in designing, implementing, and optimizing advanced imaging and computer vision solutions. They act as a technical lead supporting Operations as well, for automated inspection, robotics, and artificial intelligence initiatives, often focusing on enhancing quality assurance, safety, and operational efficiency in manufacturing, logistics, material handling environments.
RESPONSIBILITIES
- Solution Architecture: Support the design of scalable, reliable vision system architectures for multi-site deployments (e.g., factories, warehouses).
- Algorithm Development: Experienced in building and optimizing AI-driven models for object detection, segmentation, tracking, and anomaly detection using frameworks like TensorFlow, PyTorch, and OpenCV.
- System Integration & Optimization: Deep knowledge of integrating cameras, lenses, and lighting components (2D and 3D) and optimizing software for low-latency inference at the edge.
- Edge & Cloud Deployment: Support deploying and optimizing computer vision models on resource-constrained devices and integrating with cloud platforms for data analytics.
- Technical Governance: Establishing best practices for data management, privacy, security, and quality standards for image/video data.
- Troubleshooting: Primary resource for troubleshooting and resolving Launch and Ramp challenges such as complex, non-standard issues with vision systems during production, such as poor image quality, lighting constraints, or calibration failures.
Knowledge, Skills and Experience
Essential:
- Technical Expertise: Deep knowledge of computer vision techniques, machine learning, and deep learning architectures.
- Hardware Knowledge: Experience with industrial cameras, specialized lighting techniques, lenses, and frame grabbers.
- Programming Skills: Proficiency in Python, C++, and containerization tools like Docker/Kubernetes.
- Experience: Typically, 10+ years specifically in computer vision, with 5+ years in enterprise-scale and greenfield industrial deployments.
Desired
- Experience with Launch of new production lines
- Experience with Launch of Gigafactories
- Experience with integrators and equipment OEMs related to all Inspection processes
- Experience with RCCA work to resolve production ramp challenges and achieving high reliability production rates
Example Certifications or training in the following areas
- Cognex: Training on In-Sight Vision Systems and spreadsheet programming
- Keyence: Completion of specialized courses on AI-based vision sensors (like the IV3 series)
Role Specific Qualifications:
- Bachelor's or master's degree in computer science, Electrical Engineering, or a related field Relevant
