Computer Vision Engineer

Computer Vision Engineer

Job Summary

We are seeking an experienced Computer Vision Engineer to join our Video Analytics team. In

this role, you will develop advanced AI-powered surveillance solutions for security applications

across various environments. Working collaboratively with cross-functional teams, you'll be

responsible for creating sophisticated algorithms that enhance security through vehicle analysis,

intrusion detection, behavioral monitoring, and object recognition in real-world security

environments.

Key Responsibilities

• Develop and optimize computer vision algorithms for security surveillance applications
• Work actively as part of the Computer Vision and Deep Learning team to train and fine-tune models
• Collaborate closely with the Data Science team for appropriate dataset curation and quality management
• Implement state-of-the-art architectures to improve detection accuracy and reduce false positives
• Solve challenging problems by fine-tuning models with large-scale datasets
• Create efficient processing pipelines for real-time analysis of multiple video streams
• Integrate computer vision systems with existing security infrastructure
• Work with the R&D team to continuously improve model accuracy and precision for CCTV camera deployments
• Develop adaptive algorithms that perform reliably in various lighting and weather conditions
• Establish comprehensive testing methodologies to validate detection performance

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related technical field
• 2+ years of hands-on experience developing computer vision applications
• Strong programming skills in Python (mandatory)
• Proficiency in training detection/classification/segmentation models with TensorFlow/PyTorch
• Strong understanding of model training dynamics with the ability to troubleshoot based on training/evaluation metrics
• Good theoretical and practical knowledge of deep learning fundamentals (CNNs, regularization techniques, etc.)
• Experience with real-time video processing and optimization techniques
• Understanding of dataset quality requirements for computer vision applications

Preferred Qualifications

• Programming experience in C++ (good to have)
• Experience with model optimization frameworks like OpenVINO and TensorRT
• Working knowledge of edge computing devices including Raspberry Pi and Jetson devices
• Experience specifically with security and surveillance applications
• Familiarity with state-of-the-art models including YOLO-series, EfficientNet/EfficientDet, etc.
• Knowledge of edge computing for video analytics
• Experience with multi-camera tracking and fusion algorithms
• Familiarity with CCTV systems and integration approaches
• Previous work on commercial security products
• Experience with anomaly detection in video streams
• Experience using Docker containers for Computer Vision/Deep Learning deployments

Technical Skills

• Computer Vision: OpenCV, image processing, feature extraction, spatial analysis
• Deep Learning: CNN architectures (YOLO, SSD, Faster R-CNN, EfficientDet), model training and fine-tuning
• Video Processing: Real-time frame analysis, motion detection, multi-object tracking
• Programming: Python (mandatory), C++ (good to have)
• ML Frameworks: PyTorch, TensorFlow with model deployment experience
• Model Optimization: OpenVINO, TensorRT for edge deployment
• Edge Platforms: Experience with Raspberry Pi, Jetson Devices (good to have)
• Dataset Management: Data curation, augmentation, and quality control
• Development Tools: Git, Docker, CI/CD pipelines
• Edge Computing: Deployment on embedded systems and edge devices.