About the job

Role Overview

Develop and deploy computer vision solutions using deep learning, image processing, and modern CV frameworks. Build production-ready systems for visual understanding and analysis.

Responsibilities

Design and implement computer vision models for object detection, segmentation, and classification

Develop image processing pipelines for enhancement, filtering, and feature extraction

Build and optimize CNN architectures for various computer vision tasks

Implement CV solutions using OpenCV for real-time image and video processing

Train and fine-tune deep learning models using PyTorch for production deployment

Optimize models for performance, accuracy, and inference speed

Collaborate with cross-functional teams to integrate CV solutions into products

Requirements

Bachelor's degree in Computer Science, Electrical Engineering, AI/ML, or related field

Strong expertise in image processing techniques and algorithms

Proven experience with CNNs and deep learning architectures (ResNet, YOLO, U-Net, etc.)

Proficiency in OpenCV for computer vision applications

Hands-on experience with PyTorch for model development and training

Strong Python programming skills

Understanding of computer vision fundamentals (feature detection, image transforms, edge detection)

Preferred

Experience with object detection frameworks (YOLO, Faster R-CNN, SSD)

Knowledge of semantic/instance segmentation techniques

Familiarity with vision transformers (ViT, DETR, SAM)

Experience with video processing and tracking algorithms

Understanding of 3D vision, depth estimation, or SLAM

Knowledge of model optimization (TensorRT, ONNX, quantization)

Experience with GPU programming and CUDA

Familiarity with cloud deployment and MLOps