Data Scientist - Generative AI

You will be joining an innovative team as a Data Scientist, where you will play a crucial role in developing and implementing cutting-edge Generative AI solutions. Your primary responsibility will be to leverage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques to create intelligent applications that drive significant business value and enhance user experiences. Key Responsibilities: - Design and implement Generative AI solutions using LLMs and RAG for various business applications, ensuring alignment with strategic goals. - Develop and maintain robust machine learning pipelines for training, evaluating, and deploying AI models, optimizing for performance and scalability. - Conduct in-depth analysis of large datasets to identify patterns, insights, and opportunities for AI-driven innovation, informing product development and business strategy. - Collaborate with cross-functional teams to integrate AI models into existing systems and workflows, ensuring seamless deployment and user adoption. - Research and evaluate new AI technologies and techniques to continuously improve capabilities and stay ahead of industry trends, driving innovation and competitive advantage. - Communicate complex technical concepts and findings to both technical and non-technical audiences, fostering understanding and collaboration. Qualifications Required: - Demonstrated expertise in developing and deploying machine learning models using Python and related libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Proven ability to work with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques. - Strong understanding of statistical modeling, data mining, and machine learning algorithms. - Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to diverse audiences. - A Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. - Ability to thrive in a fast-paced, dynamic environment and adapt to evolving project requirements. You will be joining an innovative team as a Data Scientist, where you will play a crucial role in developing and implementing cutting-edge Generative AI solutions. Your primary responsibility will be to leverage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques to create intelligent applications that drive significant business value and enhance user experiences. Key Responsibilities: - Design and implement Generative AI solutions using LLMs and RAG for various business applications, ensuring alignment with strategic goals. - Develop and maintain robust machine learning pipelines for training, evaluating, and deploying AI models, optimizing for performance and scalability. - Conduct in-depth analysis of large datasets to identify patterns, insights, and opportunities for AI-driven innovation, informing product development and business strategy. - Collaborate with cross-functional teams to integrate AI models into existing systems and workflows, ensuring seamless deployment and user adoption. - Research and evaluate new AI technologies and techniques to continuously improve capabilities and stay ahead of industry trends, driving innovation and competitive advantage. - Communicate complex technical concepts and findings to both technical and non-technical audiences, fostering understanding and collaboration. Qualifications Required: - Demonstrated expertise in developing and deploying machine learning models using Python and related libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Proven ability to work with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques. - Strong understanding of statistical modeling, data mining, and machine learning algorithms. - Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to diverse audiences. - A Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. - Ability to thrive in a fast-paced, dynamic environment and adapt to evolving project requirements.