Senior Computer Vision Engineer

SeeWise.AI; Chennai District; On-site; INR 2,800,000 - 4,400,000; Full time

Job summary

SeeWise.AI is seeking a Senior Computer Vision Engineer with 6+ years of hands-on experience to build and deploy AI-powered quality inspection solutions for industrial environments.

You will own end-to-end vision systems from image capture to model deployment, optimization, and production validation, collaborating with production and quality teams.

The role emphasizes real-time inference, camera integration, and robust defect detection across multiple cameras and lighting conditions.

Qualifications

• 6+ years of hands-on Computer Vision / Deep Learning experience.
• Strong Python programming.
• Experience with production deployment of CV models.
• Familiarity with industrial cameras and image acquisition.
• Knowledge of evaluation metrics and model validation.

Responsibilities

• Lead R&D in Computer Vision product development.
• Design CV solutions for quality inspection and defect detection.
• Train and evaluate deep learning models for detection and segmentation.
• Build datasets and define annotation requirements.
• Deploy and optimize CV models for real-time production.
• Work with industrial cameras and video streams.
• Collaborate with production and quality teams to translate requirements.

Skills

Python

Deep Learning

PyTorch

TensorFlow

Object detection

Image segmentation

Production deployment

GPU acceleration

Camera systems

Tools

OpenCV

ONNX

CUDA

Job description

We are looking for a Senior Computer Vision Engineer with 6+ years of hands-on experience in developing and deploying AI-based Quality Inspection and Computer Vision solutions for industrial environments. This role involves owning end-to-end vision systems, from image acquisition and model development to deployment, optimization, and production validation.

Key Responsibilities

• Lead R&D efforts in Computer Vision product development, guide junior engineers, and take ownership of product development
• Design and develop Computer Vision solutions for automated quality inspection and defect detection
• Develop and train Deep Learning models for object detection, image classification, semantic / instance segmentation, and visual anomaly detection
• Build datasets, define annotation requirements, perform data augmentation, and evaluate model performance
• Apply OpenCV and classical image processing techniques for preprocessing, feature extraction, measurement, filtering, and post-processing
• Perform model validation and error analysis using precision, recall, false positives, false negatives, and defect-level performance
• Develop complete QC pipelines combining model predictions with inspection and business logic
• Deploy and optimize Computer Vision models for real-time production environments
• Work with industrial cameras, IP cameras, and video streams, including image acquisition, camera calibration, perspective correction, and ROI configuration
• Troubleshoot real-world inspection challenges involving lighting, lens selection, exposure, motion blur, reflections, camera positioning, product variations, and defect appearance
• Work closely 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

Requirements

• 6+ years of hands-on experience in Computer Vision / Deep Learning, with strong experience in industrial applications
• Strong programming skills in Python
• Strong understanding of Computer Vision and Deep Learning fundamentals
• Hands-on experience with PyTorch / TensorFlow and OpenCV or equivalent frameworks
• Experience with modern object detection and segmentation architectures
• Strong understanding of model training, validation, performance metrics, and inference pipelines
• Experience deploying trained Computer Vision models into production applications
• Familiarity with GPU-based inference and model optimization
• Experience working with industrial cameras and integrating vision systems into production environments
• Prior experience building and deploying Computer Vision-based QC / automated inspection systems in production
• Experience with manufacturing defects, surface defects, dimensional abnormalities, or other product-quality inspection use cases

Preferred Experience

• Experience with multi-camera vision systems
• Experience with TensorRT, ONNX, NVIDIA GPUs, Jetson, or similar edge deployment platforms
• Experience with industrial automation, PLC integration, or manufacturing-line systems
• Experience optimizing Computer Vision pipelines for real-time inference
• Experience with Vision Transformers or newer Computer Vision architectures
• Exposure to Vision-Language Models (VLMs) for industrial or visual inspection applications
• Experience handling limited or imbalanced defect datasets