LLA_Senior Computer Vision / AI Engineer (Smart Manufacturing)

About the Role

We are seeking an experienced Computer Vision / AI Engineer with at least 3+ years of hands-on experience to lead and scale our intelligent inspection systems. In this role, you will design, train, and deploy robust deep learning and computer vision pipelines directly onto factory production lines to automate quality control, optimize yield, and reduce downtime.
Proven, hands-on experience in visual defect detection (Automated Optical Inspection / AOI) in an industrial or manufacturing environment is a strict prerequisite for this position.

Key Responsibilities

• Algorithm & Model Development: Design, benchmark, and optimize state-of-the-art computer vision models for surface defect detection, classification, segmentation, and anomaly detection.
• Factory Deployment & Edge Inference: Package and deploy models onto edge computing devices and industrial IPCs, ensuring ultra-low latency, high throughput, and deterministic performance.
• Optical & Hardware Integration: Collaborate closely with mechanical, and optical teams to calibrate industrial cameras, lenses, lighting configurations, and image triggering protocols.
• Data Lifecycle Management: Build and manage data ingestion pipelines, active learning workflows, defect annotation protocols, and to resolve class imbalance issues.
• Production Monitoring & MLOps: Implement monitoring systems to track model drift, false reject rates (overkill), and escape rates (underkill); build automated retraining and validation pipelines.
• Cross-Functional Collaboration: Partner with process engineers, quality assurance (QA) teams, and shop-floor technicians to translate physical defect criteria into actionable machine vision specifications.

Minimum Qualifications (Must-Have)

• Experience: Minimum of 3+ years of professional experience applying Computer Vision and Deep Learning in a commercial or industrial production setting.
• Mandatory Domain Expertise: Direct, proven track record delivering end-to-end visual defect detection (AOI/AVI) projects from offline POC to 24/7 continuous factory line integration.
• Technical Stack:

o Proficiency in Python.
o Deep expertise with core DL frameworks: PyTorch or TensorFlow.
o Mastery of computer vision libraries: OpenCV, Scikit-Image, or equivalent.
o Practical knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) and CI/CD pipelines.

• Edge & Inference Optimization: Practical experience converting and accelerating models using runtimes such as TensorRT, ONNX Runtime, or OpenVINO.
• Education: Master’s degree in Computer Science, Electrical Engineering, Mathematical, Data Science, or a related quantitative discipline (or equivalent practical experience).