AI Research Scientist - LLM / GenAI

Job Description

We are seeking an innovative and highly motivated AI Research Scientist with expertise in Large Language Models (LLMs) and Generative AI (GenAI) to join our cutting-edge AI research team. As a core member of the team, you will contribute to pioneering research, develop state-of-the-art models, and help push the boundaries of AI technologies. The ideal candidate will have a deep understanding of machine learning, natural language processing (NLP), and generative models, with a passion for tackling complex problems and advancing AI. Key Responsibilities: Conduct Original Research: Lead research in the areas of LLMs, Generative AI, and NLP to propose novel algorithms, architectures, and methodologies that advance the state of the art. Model Development & Implementation: Design, develop, and experiment with advanced models, focusing on scaling, fine-tuning, and improving large language models for various applications, such as text generation, summarization, translation, and dialogue systems. Collaboration: Work closely with cross-functional teams (data science, engineering, product, etc.) to translate research ideas into production-ready solutions. Publications & Thought Leadership: Publish papers in top-tier conferences and journals (e.g., NeurIPS, ICML, ACL, CVPR). Present research at industry events and stay at the forefront of the latest advancements in AI. Model Evaluation & Benchmarking: Define metrics, evaluate model performance, and optimize the efficiency and scalability of LLMs and GenAI systems. Experimentation: Conduct rigorous experiments to analyze model behavior and improve robustness, fairness, and generalization. Mentorship: Provide guidance and mentorship to junior researchers and team members. Required Qualifications: PhD or Masters in Computer Science, AI, Machine Learning, or a related field. Strong background in Natural Language Processing (NLP) , Deep Learning , and Generative AI . Proficiency in Deep Learning frameworks such as PyTorch, TensorFlow, or JAX. Proven experience with Large Language Models (LLMs) , transformer-based architectures (e.g., GPT, BERT, T5), and related NLP techniques. Strong programming skills in Python , with experience in relevant libraries (e.g., Hugging Face Transformers, TensorFlow, PyTorch). Solid understanding of optimization techniques, model training, and scaling large models. Experience with distributed computing , cloud platforms (AWS, GCP, Azure), and parallel processing techniques. Demonstrated experience in research publications in top-tier AI/ML conferences and journals. Preferred Qualifications: Experience in Large Language Models (LLMs) . Understanding of AI ethics , fairness, bias mitigation, and explainability in AI models.. Strong publication record in areas like Generative Models , Self-Supervised Learning , Transfer Learning , etc.