Data Scientist (6+ Years)

About the Role We are looking for a Data Scientist with 6+ years of experience in AI/ML and Generative AI to build scalable, enterprise-grade intelligent solutions. The ideal candidate will have hands-on experience in Deep Learning, NLP, Large Language Models (LLMs), AI Agents, RAG pipelines, and cloud-native AI deployments. You will work closely with cross-functional teams to design, develop, and deploy innovative AI applications using modern frameworks and technologies. Experience: 6+ Years Employment Type: Full-Time Location: Bengaluru (Onsite) Key Responsibilities Design, develop, and deploy AI/ML and Generative AI solutions for enterprise applications. Build and optimize NLP models, RAG pipelines, and agentic AI workflows. Develop AI agents using frameworks such as LangGraph and implement prompt engineering workflows for LLMs including GPT, Claude, and LLaMA. Work with large-scale image and video datasets, including data preprocessing and augmentation techniques. Build and fine-tune deep learning models using TensorFlow and PyTorch. Collaborate with cross-functional teams to develop scalable and production-ready AI solutions. Implement MLOps best practices, including model versioning, CI/CD pipelines, and automated model deployment. Work with Databricks, Azure cloud services, and UNIX/Linux environments to build and deploy AI applications. Required Skills & Qualifications 6+ years of experience in Data Science or related AI/ML domains. Strong proficiency in Python and modern software development practices. Hands-on experience with TensorFlow and/or PyTorch. Strong understanding of NLP techniques, Transformer architectures, RNNs, Transfer Learning, and Vision Transformer (ViT) models. Experience building Generative AI applications, including RAG pipelines and agentic workflows. Hands-on experience with AI agent frameworks such as LangGraph. Experience designing and optimizing prompt engineering workflows for LLMs. Strong expertise in Databricks and the Azure cloud ecosystem. Experience with MLOps practices, including CI/CD pipelines, model versioning, and automated deployments. Proficiency working in UNIX/Linux environments and scripting tools. Preferred Skills Exposure to Convolutional Neural Networks (CNNs) and Reinforcement Learning. Knowledge of enterprise AI security, compliance, and governance practices. Strong analytical, communication, and collaboration skills with the ability to work effectively in cross-functional teams.