Senior Data Scientist

You are seeking a highly skilled and motivated Data Scientist with expertise in Generative AI and Large Language Models (LLM). Your role will involve transitioning from promising hypotheses and ML experiments to fully-fledged AI/ML products with real-world impact. As a specialist in Generative AI techniques, you will work with both closed and open-source Gen AI models, apply standard methodologies in prompt engineering, RAG applications, and fine-tune LLM models to drive business outcomes. Responsibilities: - Develop and implement machine learning models, focusing on Generative AI techniques and LLM, to solve sophisticated business problems, using various algorithms and techniques. - Streamline Generative AI model development and deployment using Azure infrastructure and capabilities such as cognitive search and Vectordb, along with frameworks like Langchain, Llama, Semantic Kernel, and Autogen. - Apply prompt engineering techniques, work with RAG applications, and fine-tune language models to enhance their performance in specific tasks. - Collaborate with multi-functional teams to plan, scope, implement, and sustain predictive analytics solutions. - Design and conduct experiments to validate and optimize machine learning models, ensuring accuracy, efficiency, and scalability. - Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration, scalability, and cost-effectiveness. - Develop measurements and feedback systems, and mentor associates and peers on MLOps & LLMOps standard methodologies. - Stay updated with the latest advancements in machine learning, generative AI, prompt engineering, RAG applications, and cloud technologies, and apply them to enhance data science capabilities. Requirements: - Hands-on experience with Gen AI-related tech stack, including Azure cognitive search, Langchain, Semantic Kernel, and agent frameworks like Autogen, Vectordb. - Experience in predictive modeling around Credit risk. - Experience in fine-tuning open-source models like Llama, Phi2 is a plus. - Experience with Open AI APIs, Fine-tuning, and Assistant APIs. - Proven experience as a Data Scientist, with a focus on machine learning, generative AI, prompt engineering, and RAG applications. - Working knowledge of Cloud, Architecture, REST APIs to deploy inferencing and fine-tuning solutions. - Strong partner management skills, ability to translate technical topics into business language, presentation skills, and a balance of urgency with shipping high-quality solutions. - Strong software development skills with proficiency in Python and advanced working SQL knowledge, preferably using the Azure stack and experience with Azure ML, Databricks, Azure Data Factory. - Experience in product-ionizing code through the DevOps pipeline (git, Jenkins pipeline, code scan). - Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.,