What you'll do:

• Strong understanding of NLP concepts, various NLP architectures, and practical applications of these architectures.
• Develop and implement NLP models, including text classification, entity recognition, and sentiment analysis.
• Work on solving real-world scenarios for user commands and requests, and build scalable systems that solve their problems.
• Experience with deep learning frameworks, such as TensorFlow or PyTorch, and NLP libraries, such as spaCy or NLTK.
• Implement and experiment with advanced NLP techniques.
• Strong problem-solving and critical thinking skills, with the ability to debug complex NLP models.
• Manage data pre-processing tasks, including tokenization and data cleaning.
• Debug and optimize existing NLP models and systems to improve accuracy and performance.
• Conduct research to stay up to date on the latest NLP advancements and incorporate new techniques into our systems.
• Collaborate on implementing and testing new approaches.
• Create clear reports and presentations.
• Experience in developing solutions using AI, and ML technology.
• Proficient with deep learning algorithms especially in developing computer vision and NLP applications
• 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 such as (speech, NLP, GANs)
• Train and fine-tune NLP models using machine learning techniques and deep learning frameworks.

What makes you a great fit:

• Must have knowledge of deep learning, NLP, and Computer Vision.
• Strong understanding of NLP concepts and techniques.
• Familiarity with NLP libraries and frameworks (e. g., NLTK, SpaCy, Transformers).
• Proficiency in Python programming.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Attention to detail and ability to work independently.
• Prior NLP project or research experience is a plus.