Job
Description
As a candidate with a strong passion for Generative AI and Natural Language Processing (NLP), you have the opportunity to join a team that is working on cutting-edge AI solutions using state-of-the-art technologies such as transformers, text generation, and sentiment analysis. Your role will involve building and fine-tuning Generative AI models, specifically focusing on NLP tasks. This is a fantastic opportunity for you to grow alongside a team of experts, tackle real-world challenges, and contribute to advancing the field of AI. Key Responsibilities: - Assist in the design and development of NLP systems for tasks such as 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 and apply 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 to ensure reproducibility and efficient knowledge sharing within the team. Technical Requirements: Must Have Skills: - Basic understanding of NLP techniques such as text classification, tokenization, sentiment analysis, and NER. - Familiarity with Generative AI concepts including GANs, transformers, and autoencoders. - Strong programming skills in Python with experience 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 Responsibilities: Nice to Have 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. Soft Skills: - Strong verbal and written communication skills with the ability to work well in a team. - Strong customer focus, ownership, urgency, and drive. - Ability to handle multiple competing priorities in a fast-paced environment. - Work well with team members to maintain high credibility. Educational Requirements: - Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or a related field required. - Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field preferred for senior roles. Location: - India As a candidate with a strong passion for Generative AI and Natural Language Processing (NLP), you have the opportunity to join a team that is working on cutting-edge AI solutions using state-of-the-art technologies such as transformers, text generation, and sentiment analysis. Your role will involve building and fine-tuning Generative AI models, specifically focusing on NLP tasks. This is a fantastic opportunity for you to grow alongside a team of experts, tackle real-world challenges, and contribute to advancing the field of AI. Key Responsibilities: - Assist in the design and development of NLP systems for tasks such as 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 and apply 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 to ensure reproducibility and efficient knowledge sharing within the team. Technical Req
