Role Overview We are looking for a Computer Vision Engineer with 6+ years of hands-on experience in developing and deploying AI-based Quality Inspection (QC) solutions and Computer Vision solutions for industrial environments. The role involves building end-to-end computer vision systems, from image acquisition and model development to deployment and production validation. Roles & Responsibilities
• Lead the R&D; team's efforts in product development, guiding juniors, and owning the product.
• Design and develop Computer Vision solutions for automated quality inspection and defect detection.
• Develop and train Deep Learning models for: o Object Detection o Image Classification o Semantic / Instance Segmentation o Visual Anomaly and Defect Detection
• Apply classical image processing techniques using OpenCV or equivalent libraries for preprocessing, feature extraction, measurement, filtering, and post-processing.
• Build datasets, define annotation requirements, perform data augmentation, and evaluate model performance.
• Perform model validation and error analysis focusing on false positives, false negatives, precision, recall, and defect-level performance.
• Develop complete QC pipelines combining model predictions with appropriate business/inspection logic.
• Deploy and optimize Computer Vision models for real-time production environments.
• Troubleshoot real-world QC challenges such as variations in lighting, reflections, camera angles, product positioning, backgrounds, and defect appearance.
• Work with production and quality teams to translate inspection requirements into practical Computer Vision solutions.
• Continuously improve deployed models based on production data and newly identified defect scenarios. Camera & Vision System Experience
• Experience working with industrial cameras, IP cameras, and video streams.




• Understanding of camera selection and compatibility based on resolution, frame rate, field of view, working distance, and inspection requirements.
• Familiarity with camera calibration, perspective correction, ROI configuration, and image acquisition.
• Understanding of the impact of lighting, lens selection, exposure, motion blur, reflections, and camera positioning on inspection accuracy.
• Experience integrating and validating cameras as part of an end-to-end QC system. Required Skills
• Strong programming experience in Python.
• Solid understanding of Computer Vision and Deep Learning fundamentals.
• Hands-on experience with PyTorch / TensorFlow, OpenCV, or equivalent frameworks.
• Experience with modern object detection and segmentation architectures.
• Understanding of model training, validation, performance metrics, and inference pipelines.
• Experience deploying trained models into production applications.
• Familiarity with GPU-based inference and model optimization. Preferred Experience
• 6+ years of experience.
• Prior experience building and deploying Computer Vision-based QC / automated inspection systems in production.
• Experience detecting manufacturing defects, surface defects, dimensional abnormalities, or product-quality issues.
• Experience with multi-camera vision systems.
• Experience with TensorRT, ONNX, NVIDIA GPUs, Jetson, or similar edge deployment platforms.
• Familiarity with industrial automation, PLC integration, or manufacturing-line systems.
• Experience optimizing Computer Vision pipelines for real-time inference. Good to Have
• Experience with Vision Transformers or newer Computer Vision architectures.
• Exposure to Vision-Language Models (VLMs) for industrial or visual inspection applications.
• Experience with synthetic data generation or handling limited/imbalanced defect datasets.
• Basic understanding of APIs, databases, Docker, and Linux-based deployment environments.

📌 Sr Computer Vision Engineer (Chennai)
🏢 Spritle Software
📍 Chennai