This person MUST have:
- B.E Computer Science or equivalent.
- In-depth knowledge of machine learning algorithms and their applications including
practical experience with and theoretical understanding of algorithms for classification,
regression and clustering.
- Hands-on experience in computer vision and deep learning projects to solve real world
problems involving vision tasks such as object detection, Object tracking, instance
segmentation, activity detection, depth estimation, optical flow, multi-view geometry,
domain adaptation etc.
- Strong understanding of modern and traditional Computer Vision Algorithms.
- Experience in one of the Deep Learning Frameworks / Networks: PyTorch, TensorFlow,
Darknet (YOLO v4 v5), U-Net, Mask R-CNN, EfficientDet, BERT etc.
- Proficiency with CNN architectures such as ResNet, VGG, UNet, MobileNet, pix2pix,
and Cycle GAN.
- Experienced user of libraries such as OpenCV, scikit-learn, matplotlib and pandas.
- Ability to transform research articles into working solutions to solve real-world problems.
- High proficiency in Python programming knowledge.
- Familiar with software development practices/pipelines (DevOps- Kubernetes, docker
containers, CI/CD tools).
- Strong communication skills. Skills:- Deep Learning, Computer Vision, PyTorch, TensorFlow, Python, OpenCV, pandas, matplotlib, RestNet, VGG, MobileNet and Pix2pix
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