AI/ML Computer Vision Engineer

Job Description

AI/ML Computer Vision Engineer (4-5 Years' Experience)Location: BangaloreJob Type: Full-timeExperience: 4-5 yearsIndustry: AI/ML, Computer Vision, Deep LearningJob Summary:We are seeking an experienced AI/ML Computer Vision Engineer with 4-5 years of hands-on experience in developing and deploying deep learning models for computer vision tasks. The ideal candidate will have a strong background in image/video processing, deep learning architectures, and real-time inference optimization. You will work on cutting-edge projects, including object detection, segmentation, pose estimation, action recognition, and generative AI applications.

Key Responsibilities

Design, develop, and optimize deep learning models for computer vision tasks such as object detection, tracking, segmentation, and classification.Work with large-scale image and video datasets, including data collection, preprocessing, augmentation, and annotation pipelines.Implement and fine-tune state-of-the-art architectures (e.g., CNNs, Vision Transformers, GANs, Diffusion Models).Develop efficient inference pipelines for deployment on edge devices (e.g., TensorRT, ONNX, OpenVINO) and cloud platforms.Collaborate with cross-functional teams to deploy AI models in production and ensure scalability, robustness, and efficiency.Stay updated with recent AI/ML research and apply best practices to improve model performance and generalization.

Requirements

Education: Bachelor’s or Master’s in Computer Science, AI, Machine Learning, Computer Vision, or related fields.Experience: 4-5 years of hands-on experience in computer vision and deep learning.Programming: Proficient in Python, with strong experience in PyTorch, TensorFlow, OpenCV, and NumPy.Deep Learning Models: Hands-on experience with CNNs, ViTs, GANs, and transformer-based architectures.Computer Vision Techniques: Image processing, object detection (YOLO, Faster R-CNN), segmentation (U-Net, Mask R-CNN), tracking (SORT, DeepSORT), pose estimation (OpenPose, HRNet)How to Apply Please apply at: https://forms.gle/1DDdhSkuQWDF2zqTA