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Deep Learning and Computer Vision Engineer
Deep Learning and Computer Vision Engineer
Charmboard's logo

Deep Learning and Computer Vision Engineer

Kavitha Joseph's profile picture
Posted by Kavitha Joseph
2 - 7 yrs
₹7L - ₹15L / yr
Bengaluru (Bangalore)
Skills
skill iconMachine Learning (ML)
Artificial Intelligence (AI)
computer vision
Description • Develop state of the art algorithms in the fields of Computer Vision, Machine Learning and Deep Learning. • Provide software specifications and production code on time to meet project milestones Qualifications • BE or Master with 3+ years of experience • Must have Prior knowledge and experience in Image processing and Video processing • Should have knowledge of object detection and recognition • Must have experience in feature extraction, segmentation and classification of the image • Face detection, alignment, recognition, tracking & attribute recognition • Excellent Understanding and project/job experience in Machine learning, particularly in areas of Deep Learning – CNN, RNN, TENSORFLOW, KERAS etc. • Real world expertise in deep learning- applied to Computer Vision problems • Strong foundation in Mathematics • Strong development skills in MATLAB and Python • Must have worked upon Vision and deep learning libraries and frameworks such as Opencv, Tensorflow, caffe, keras • Quick learner of new technologies • Ability to work independently as well as part of a team • Knowledge of working closely with Version Control(GIT)
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About Charmboard

Founded :
2014
Type :
Product
Size :
100-500
Stage :
Raised funding

About

Charmboard, owned by Tagos Innovations, provides a technology that turns any video into an interactive experience, allowing the viewer to touch or click on any item to receive additional information. This includes information about the object or product, direct links to company websites and the ability to buy that item directly. Also, provides a platform that uses an algorithm that detects potential surfaces in the video which can be used as ad space and integrate the ads. Graduated from the Target Accelerator Program in October 2016. Raised $5M in a Series A round of funding from undisclosed investors in June 2017.
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Shubham Vishwakarma

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