Responsibility: + Build and enhance machine learning models through all phases of development including design, training, validation, and implementation etc. + Unlock insights by analyzing large scale of complex numerical and textual data and identifying trends. + Partner with a cross-functional team of data engineers, data scientists, and data visualization to deliver projects. + Research and evaluate emerging technologies. + Develop data science solutions based on tools and cloud computing infrastructure. + Perform other duties as assigned. Qualifications: + Bachelor's degree in computer science, mathematics, physics, statistics, or related field. + Strong experience with applying expertise in model design, training, validation, and monitoring. + Excellent understanding of machine learning, statistical modeling, and algorithms as well as their benefits and drawbacks. + Advanced skills with Python, Jupyter Notebook/Jupyter Lab, Visual Studio Code and other languages appropriate for large data analysis. + Experience with cloud computing infrastructure. + Advanced SQL skills. + Experience with data visualization concepts and tools. + Ability to convey complex business problems to technical solutions. + Ability to work individually, and as part of a team. + Advanced verbal, written, interpersonal, and presentation skills to communicate clearly and concisely technical and non-technical information to all levels of management. Desired: + Advanced degree in in computer science, mathematics, physics, statistics, or related field. + Experience with Natural Language Processing. + Experience with deep learning framework and infrastructure like TensorFlow or PyTorch. + Experience and/or willing to learn techniques in Large Language Models (LLMs) and Generative AI. + A.I. Model Optimization on GPU architecture. Leveraging C++, CUDA. + Experience and/or willing to research, develop, implement, and fine-tuning LLMs in terms of specific domains knowledge and user cases. + Knowledge of Machine Learning Ops and CI/CD tools for automation of build, test, and deploy models in production environments.