About Me
Computer Vision Engineer with 2+ years of experience designing, training, and deploying real-time computer vision and deep learning systems using Python, OpenCV, YOLO, MediaPipe, and PyTorch. Skilled across the full CV p…
Computer Vision Engineer with 2+ years of experience designing, training, and deploying real-time computer vision and deep learning systems using Python, OpenCV, YOLO, MediaPipe, and PyTorch. Skilled across the full CV pipeline: data preprocessing, model training, real-time inference optimization, and lightweight API deployment. Delivered production gesture recognition, facial emotion recognition, and object detection/tracking systems with measurable gains in accuracy, latency, and user experience. Strong foundation in machine learning (SVM, KNN, K-Means, Logistic Regression) and CNN-based deep learning.
Experience
Computer Vision Engineer
<p>Designed and deployed a real-time Hand Gesture Recognition System using Python, OpenCV, and MediaPipe, achieving 90%+ classification accuracy across 10+ gesture classes.</p><p> Built a touchless interaction application processing live webcam input at 25–30 FPS, enabling gesture-based control without physical hardware.</p><p> Engineered the image preprocessing and feature extraction pipeline (hand landmark detection, normalization), reducing false-positive detections by an estimated 20%.</p><p> Optimized inference performance through frame-skipping and model tuning, cutting end-to-end latency by roughly 30% for a smoother user experience.</p><p> Collaborated with a cross-functional engineering team to design, test, and deploy production-ready computer vision applications.</p>
Computer Vision Engineer
<p>Developed a Facial Emotion Recognition System using Python, OpenCV, and Machine Learning, reaching approximately 85% accuracy across 6–7 emotion classes on live video.<br>
Implemented a face detection and facial-expression classification pipeline trained on a labeled dataset of 5,000+ facial images.<br>
Built Human-Computer Interaction (HCI) features on top of the emotion model to support real-time user-state feedback.<br>
Contributed to AI model development, testing, and integration into the broader software application.</p>