Data Scientist - Artificial Intelligence

Data Scientist Artificial Intelligence (AI/ML) Experience: 5-8 Years Location: Bangalore Interview- F2F Only Job Summary We are seeking a highly skilled Data Scientist Artificial Intelligence with strong expertise in Generative AI, Machine Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agent frameworks . The ideal candidate will have hands-on experience designing, developing, and deploying AI-powered applications using modern AI frameworks and cloud technologies. You will work closely with cross-functional teams to build intelligent AI solutions, optimize model performance, and develop scalable AI systems that solve real-world business problems. Key Responsibilities Design, develop, and deploy AI/ML solutions for enterprise applications. Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models. Develop multi-step AI agent architectures capable of planning, reasoning, tool usage, and workflow automation. Fine-tune, evaluate, and deploy Large Language Models (LLMs) for domain-specific use cases. Develop NLP and Generative AI applications including chatbots, document intelligence, knowledge assistants, and automation platforms. Work with structured and unstructured datasets for feature engineering, preprocessing, and model development. Implement prompt engineering strategies to improve AI model accuracy and response quality. Integrate AI models with enterprise applications using REST APIs and microservices. Collaborate with Data Engineers, Software Engineers, and Product teams throughout the AI solution lifecycle. Optimize model inference, latency, scalability, and production performance. Monitor AI models, evaluate quality metrics, and implement continuous improvements. Stay updated with emerging AI technologies, research, and industry best practices. Required Skills Artificial Intelligence & Machine Learning Strong understanding of Machine Learning and Deep Learning algorithms. Experience with supervised, unsupervised, and reinforcement learning. Experience in NLP, text processing, and transformer-based models. Knowledge of model evaluation, feature engineering, and model optimization. Generative AI Hands-on experience with Large Language Models (LLMs) . Experience designing and deploying RAG (Retrieval-Augmented Generation) pipelines . Experience building multi-agent or multi-step AI agent architectures . Strong understanding of prompt engineering techniques. Experience with embeddings and semantic search.