Data Scientist - Artificial Intelligence/Machine Learning

Role Overview

• Design, develop, and fine-tune advanced Generative AI models such as LLMs, GANs, and Diffusion models.
• Implement and enhance RAG and transformer-based architectures for contextual understanding and document intelligence.
• Customize and optimize LLMs for specific domain applications.
• Build, maintain, and optimize ML pipelines and infrastructure for model training, evaluation, and deployment.
• Collaborate with engineering teams to integrate AI models into user-facing applications.
• Stay updated with the latest trends and research in Generative AI, open-source frameworks, and tools.
• Analyze model outputs for quality and performance, ensuring adherence to ethical AI Skills :
• Strong proficiency in Python and deep learning frameworks including TensorFlow, PyTorch, and HuggingFace Transformers.
• Deep understanding of GenAI architectures including LLMs, RAG, GANs, and Autoencoders.
• Experience with fine-tuning models using techniques such as LoRA, PEFT, or equivalents.
• Knowledge of vector databases (e.g., FAISS, Pinecone) and embedding generation methods.
• Experience handling datasets, preprocessing, and synthetic data generation.
• Solid grasp of NLP concepts, prompt engineering, and safe AI practices.
• Hands-on experience with API development, model deployment, and cloud platforms (AWS, GCP, Azure).