Computer Vision Engineer
Work with the best talent of software engineers and scientists to design and implement cutting edge technologies. Train machine learning and deep learning models on a computing cluster to perform visual recognition tasks, such as segmentation and detection. Enjoy access to large proprietary data, run experiments, learn, iterate and ship.
We are continuously striving to be ahead of the curve through their cutting-edge technology. This is reflected through our various virtual and in-person learning interventions. We focus on developing engineering, management and life skills.
This is reflected through our hiring process, we are constantly looking for candidates who are at ease experimenting with new technologies, make bold bets, take ownership and are nimble in their approach.
- Build computer vision algorithms on resource constrained devices
- Work on cutting edge problems in Deep Learning for Internal AI Accelerator SW Stack
- Develop & integrate functional and performance models of accelerators
- Analyzing the accuracy of Neural Network on Functional models and correlate with HW implementation
- Be part of discussions in defining the next gen HW accelerators
- Research on various numerics related to Machine Learning, optimizing it based on design and performance constraints
- Experience in embedded Computer Vision (Open CV), SIMD and parallel computing, with a deep understanding of CV algorithms and multimedia image formats
- Fluent in working with Python
- Fluent in C and C++ as well as experience in CUDA
- Efficient in SW development in Linux, with a deep understanding of operating system e.g. Linux,
- Good knowledge in SoCs e.g. Tegra, with efficient use of Software development tools like debuggers
- Excellent written and verbal interpersonal skills and an eye for detail
- Good organization skills, with a logical approach to problem-solving, time management and ability to prioritise
- Experience with visual geometry and deep learning in a shipping product context
- Worked on real-time Image Processing and/or computer vision systems
- Software development on embedded platforms or large scale cloud services
- Experience with GPGPU programming (CUDA and OpenGL)
- Worked on atleast one mainstream deep learning frameworks, including TensorFlow, Caffe(2), MXNet, PyTorch.