AddressAbout the Company :
AjnaLens is a Human-First Organization. Named after 'Ajna', the sixth chakra or the third eye, AjnaLens 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, AjnaLens has built state-of-the-art immersive learning solutions to help governments, education institutes and fortune 500 companies in their digital transformation journey.
AjnaLens is trusted by 30+ prestigious clients like the Indian Army, Indian Navy, DRDO, Ministry of Defence, Vedanta, L&T, and Tata Technologies among others.
AjnaLens has filed 20+ patents in augmented reality, virtual reality and allied fields.
Job role : Senior AI/CV : 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.
- 8+ Years of relevant Experience
- At least 2+ years of experience in Deep Learning and Machine Learning techniques.
- At least 1+ 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 GitHub Repos.
- Hands-on with popular deep learning frameworks- Keras, TensorFlow, PyTorch 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.
- 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.
