Responsibilities:
Design, manage, and enhance an on-premise hardware platform to support AI, Machine Learning, and Large Language Model applications. Work closely with data scientists and development teams to seamlessly integrate AI and machine learning models into the infrastructure. Utilize foundational knowledge of frameworks like PyTorch, TensorFlow, and NumPy to test and deploy AI/ML models from various teams. Develop and maintain DevOps-driven container solutions for AI and ML workloads using tools such as Docker, Kubernetes, and virtualization technologies like VMware. Implement and optimize CI/CD pipelines for efficient container deployment, ensuring hardware-accelerated performance for AI applications. Qualifications:
Bachelor/Master's  Expert knowledge on Container technologies (Donker, Kubernetes) Experience with Data Scientists Knowledge of CI/CD Pipelines, Deploying AI & Machine Learning