Generative AI and Natural Language Processing (NLP)

Role Overview: You will have the opportunity to learn and contribute to the development of cutting-edge AI solutions focusing on Generative AI and Natural Language Processing (NLP). As part of the team, you will work with state-of-the-art technologies such as transformers, text generation, and sentiment analysis. This role offers a great chance to grow alongside experts, tackle real-world challenges, and advance the field of AI. Key Responsibilities: - Assist in designing and developing NLP systems for tasks like text classification, sentiment analysis, named entity recognition (NER), and machine translation. - Contribute to the development of language models for text summarization, question answering, and dialog systems. - Work with large unstructured text datasets applying techniques such as text preprocessing, tokenization, and embedding generation. - Collaborate with team members to develop AI-driven solutions involving transformer-based models, text generation, and other cutting-edge NLP techniques. - Continuously improve knowledge of emerging AI and NLP trends, techniques, and technologies. - Participate in learning programs and research to deepen expertise in transformer models, LLMs, RAG, and other relevant techniques. - Maintain clear and organized documentation of models, experiments, code, and results for reproducibility and efficient knowledge sharing within the team. Qualification Required: - Basic understanding of NLP techniques like text classification, tokenization, sentiment analysis, and named entity recognition (NER). - Familiarity with Generative AI concepts including GANs, transformers, and autoencoders. - Strong programming skills in Python using libraries like NumPy, Pandas, TensorFlow, PyTorch, and Hugging Face for model building and data manipulation. - Knowledge of machine learning algorithms and basic model evaluation techniques. - Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) or basic cloud concepts for model training and deployment. - Willingness to learn and work with GPU/TPU computing for efficient model training and inference. Additional Details of the Company: The company is based in India. Preferred Skills: - Familiarity with Agentic AI concepts or exposure to intelligent agent-based systems. - Exposure to working with open-source LLMs (e.g., Hugging Face) and transformer-based models. - Understanding of Docker for containerizing applications and models. - Exposure to AutoML frameworks or transfer learning techniques. - Familiarity with version control systems like Git. - Understanding of basic MLOps concepts for deploying machine learning models in production. - Interest in AI deployment tools such as Flask, FastAPI, Django, etc., for serving models in real-world applications.,