Senior computer vision engineer

2 weeks ago

Thane, India AjnaLens Full time
About the Company:
Ajna Lens is a Human-First Organization. Named after ‘Ajna’, the sixth chakra or the third eye, Ajna Lens strives to transform the lives of humans and help them unleash their true potential. The impact-driven startup is on a mission to create a skill-first world with equal economic opportunities by redefining learning and human development.
Over the years, Ajna Lens has built state-of-the-art immersive learning solutions to help governments, education institutes and fortune 500 companies in their digital transformation journey.
Ajna Lens is trusted by 30+ prestigious clients like the Indian Army, Indian Navy, DRDO, Ministry of Defence, Vedanta, L&T, and Tata Technologies among others.
Ajna Lens has filed 20+ patents in augmented reality, virtual reality and allied fields.
Job role: Senior AI/CV Engineer
Location: Thane (Work from Office)
Key responsibilities:
Working towards ideating, implementing, and optimizing deep learning models for various computer vision applications including but not limited to-
3d object detection
6d of object pose estimation.
Object tracking
3d object registration (rigid or non-rigid)
Motion capture etc.
Desired Candidate Profile:
4 to 8 Years of relevant Experience.
At least 2 years of experience in Deep Learning and Machine Learning techniques.
At least 2 years of experience in Computer Vision related applications.
Experience solving analytical problems using quantitative approaches.
Ability to manipulate and analyze large scale, high-dimensionality data from varying sources.
Expert knowledge in the following programming/scripting languages(C++, bash and Python).
Demonstrable background in Computer vision and Deep learning as open-source Git Hub Repos.
Hands-on with popular deep learning frameworks- Keras, Tensor Flow, Py Torch and Caffe.
Hands-on experience on AWS, and other cloud platforms.
Ability to implement deep learning architectures in state-of-the-art deep learning research papers.
Preferred Qualification:
Basic understanding of Natural language processing and Computer vision.
Ability to handle large and complex unstructured datasets.
Experience in optimization of deep learning pipeline for different hardware platforms.
Experience in conversion of models to formats that are compatible with mobiles.

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