Deep Learning/Computer Vision Engineers

Tata Elxsi, the forefront of the latest advancements in AI technology, where the team of passionate individuals are dedicated to making a real-world impact through innovative implementation. Here, you will find a group of like-minded individuals who are continuously exploring new AI techniques and technologies to improve the accuracy, efficiency, and scalability of our models. What sets us apart is our collaborative approach, allowing for free experimentation and quick iterations to arrive at the best solutions. We are in search of someone who shares the same passion and drive as us, and is excited about the opportunity to make a meaningful difference in the field of AI. Join us in our pursuit of advancing AI to the next level and make the future of 'AM PM AI' a reality.

We are looking for bright and passionate Deep Learning Engineers with experience in

• Experience of developing solutions using AI & ML technology
• Proficient with deep learning algorithms especially towards developing computer vision applications
• Excellent knowledge of FCN, CNN, DNN and sequential neural network architectures.
• Strong experience in using both basic and advanced image processing algorithms for feature engineering
• Ability to read and implement related academic literature and experience in applying state-of-the-art deep learning models to computer vision (e.g. segmentation, detection) or other areas as (speech, NLP, GANs)
• Knowledge on sensors and vision systems, sensor integration and fusion
• Proven expertise in developing and training state-of-the-art algorithms to perform visual recognition tasks, such as segmentation, detection, and classification at scale
• Proven expertise in Integrating deep neural networks and the associated preprocessing and postprocessing code to run efficiently on embedded platforms, including different GPU architectures
• Profound and proven knowledge in tools and programming languages like TensorFlow, KERAS, Tytorch, Matlab, Python; knowledge in embedded C/C++ is an advantage.
• Strong experience with data science tools including Python scripting, CUDA, numpy, scipy, matplotlib, scikit-learn, bash scripting and Linux environment.
• Proficiency with edge computing principles and architecture on commonly used popular platforms
• Experience in different model optimization techniques apart from hyperparameter tuning to reduce memory usage without hindering the performance for deploying on edge devices.