Data Scientist with Gen AI

As a GenAI & Data Science Engineer, you will be responsible for building AI/ML solutions, developing Generative AI applications, analyzing large datasets, and deploying scalable machine learning models. Key Responsibilities: - Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs). - Build AI-powered applications using Python and AI frameworks. - Develop and optimize Machine Learning and Deep Learning models. - Work with structured and unstructured datasets for data analysis and predictive modeling. - Implement NLP techniques including text classification, sentiment analysis, summarization, and chatbot development. - Fine-tune and customize foundation models for business use cases. - Create RAG (Retrieval-Augmented Generation) pipelines using vector databases. - Develop and maintain data pipelines for data ingestion, transformation, and processing. - Collaborate with business stakeholders to understand requirements and deliver AI-driven solutions. - Monitor model performance and continuously improve accuracy and efficiency. Qualifications Required: - Strong programming experience in Python. - Experience in Data Science, Machine Learning, and Deep Learning. - Hands-on experience with Generative AI and LLMs. - Knowledge of Prompt Engineering and AI model optimization. - Experience with LangChain, LlamaIndex, Hugging Face, OpenAI APIs, Gemini APIs, or Anthropic Claude. - Experience with Vector Databases such as Pinecone, ChromaDB, FAISS, or Weaviate. - Strong understanding of NLP techniques. - Experience with Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch. - Knowledge of SQL and database concepts. - Experience with cloud platforms such as AWS, Azure, or GCP. As a GenAI & Data Science Engineer, you will be responsible for building AI/ML solutions, developing Generative AI applications, analyzing large datasets, and deploying scalable machine learning models. Key Responsibilities: - Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs). - Build AI-powered applications using Python and AI frameworks. - Develop and optimize Machine Learning and Deep Learning models. - Work with structured and unstructured datasets for data analysis and predictive modeling. - Implement NLP techniques including text classification, sentiment analysis, summarization, and chatbot development. - Fine-tune and customize foundation models for business use cases. - Create RAG (Retrieval-Augmented Generation) pipelines using vector databases. - Develop and maintain data pipelines for data ingestion, transformation, and processing. - Collaborate with business stakeholders to understand requirements and deliver AI-driven solutions. - Monitor model performance and continuously improve accuracy and efficiency. Qualifications Required: - Strong programming experience in Python. - Experience in Data Science, Machine Learning, and Deep Learning. - Hands-on experience with Generative AI and LLMs. - Knowledge of Prompt Engineering and AI model optimization. - Experience with LangChain, LlamaIndex, Hugging Face, OpenAI APIs, Gemini APIs, or Anthropic Claude. - Experience with Vector Databases such as Pinecone, ChromaDB, FAISS, or Weaviate. - Strong understanding of NLP techniques. - Experience with Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch. - Knowledge of SQL and database concepts. - Experience with cloud platforms such as AWS, Azure, or GCP.