Senior Data Scientist - Generative AI

As a Senior Data Scientist GenAI, you will be responsible for leading the design, development, and deployment of advanced AI and Generative AI solutions. Your role will involve deep hands-on expertise across the entire AI lifecycle, from data engineering and model development to production deployment and team leadership. Key Responsibilities: - Lead end-to-end GenAI solution development from data preprocessing to production deployment - Design and implement LLM, VLM, RAG, and Agentic AI systems - Build and optimize ML/DL models using modern and core techniques - Apply NLP, Transformers, and prompt engineering for enterprise use cases - Deploy scalable AI solutions using FastAPI/Flask with cloud infrastructure - Implement MLOps best practices including CI/CD, Docker, and monitoring - Drive predictive analytics use cases including time series and forecasting - Collaborate with customers and stakeholders to translate business needs into AI solutions - Lead, mentor, and manage high-performing data science teams Required Skills & Qualifications: - 10 to 15 years of experience in Data Science with a strong focus on GenAI - Hands-on expertise in Python, TensorFlow, PyTorch, and Keras - Strong experience with LLMs, RAG pipelines, and Agentic AI architectures - Solid understanding of ML, DL, NLP, Transformers, and Computer Vision (CNNs) - Experience in production ML, MLOps, and cloud deployment (AWS / Azure) - Exposure to data engineering platforms such as Azure, ADF, and Databricks - Proven experience in customer-facing roles and team handling - Excellent communication skills; grounded, delivery-driven mindset As a Senior Data Scientist GenAI, you will be responsible for leading the design, development, and deployment of advanced AI and Generative AI solutions. Your role will involve deep hands-on expertise across the entire AI lifecycle, from data engineering and model development to production deployment and team leadership. Key Responsibilities: - Lead end-to-end GenAI solution development from data preprocessing to production deployment - Design and implement LLM, VLM, RAG, and Agentic AI systems - Build and optimize ML/DL models using modern and core techniques - Apply NLP, Transformers, and prompt engineering for enterprise use cases - Deploy scalable AI solutions using FastAPI/Flask with cloud infrastructure - Implement MLOps best practices including CI/CD, Docker, and monitoring - Drive predictive analytics use cases including time series and forecasting - Collaborate with customers and stakeholders to translate business needs into AI solutions - Lead, mentor, and manage high-performing data science teams Required Skills & Qualifications: - 10 to 15 years of experience in Data Science with a strong focus on GenAI - Hands-on expertise in Python, TensorFlow, PyTorch, and Keras - Strong experience with LLMs, RAG pipelines, and Agentic AI architectures - Solid understanding of ML, DL, NLP, Transformers, and Computer Vision (CNNs) - Experience in production ML, MLOps, and cloud deployment (AWS / Azure) - Exposure to data engineering platforms such as Azure, ADF, and Databricks - Proven experience in customer-facing roles and team handling - Excellent communication skills; grounded, delivery-driven mindset