Role & responsibilities Conduct research in AI, focusing on LLMs, NLP, and Graph-based approaches Design and implement innovative algorithms and models to improve AI capabilities Collaborate with cross-functional teams to apply research findings to real-world applications Stay current with the latest advancements in AI and contribute to the company's intellectual property portfolio Key Skills : Large Language Models (e.g., Transformer architectures, few-shot learning, prompt engineering) Natural Language Processing (e.g., text classification, named entity recognition, sentiment analysis) Graph Neural Networks and graph-based machine learning Distributed computing and parallel processing Data analysis and visualization Scientific writing and presentation skills Required Qualifications: B. Tech / Masters in Computer Science, Artificial Intelligence, or a related field Prefer a Ph.D. in Computer Science, Artificial Intelligence, or a related field Strong background in machine learning, deep learning, and AI algorithms Experience in NLP techniques and Large Language Models Experience with Graph Neural Networks and graph-based machine learning approaches Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) Excellent programming and software engineering skills Preferred Qualifications: Ph.D. in Computer Science, Artificial Intelligence, or a related field Experience with distributed computing and large-scale machine learning systems Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure) Knowledge of ethical AI and responsible AI development practices Experience with multi-modal AI systems combining language, vision, and other modalities