You should have hands-on working knowledge of AI frameworks such as PyTorch/TensorFlow, Transformers, CV2, and HuggingFace
You should have hands-on working knowledge, training, and prediction of NLP models such as Spacy, GliNER, and Reading Comprehension QA models
You should have hands-on working knowledge of common Python/AI libraries such as torch, numpy, nltk, pillow, etc. Working knowledge of Computer Vision concepts and Vision and Sentence Encoder/Decoder models is a BIG plus
You should care about Performance, High availability, and Scalability will get to work on building key elements of a Knowledge Analytics solution, including the state-of-the-art AI models encompassing Computer Vision, Natural Language Processing, and Machine learning technologies
Ontology-based domain modeling: Processing data with Knowledge Graph
