Job description: We are looking for an experienced distributed deep learning engineer to drive cutting-edge decentralized artificial intelligence and machine learning projects. The ideal candidate should have extensive experience in deep learning frameworks, model training and optimization, containerization and orchestration techniques, as well as cloud computing platforms. Experience in CUDA programming, multi GPU communication optimization, and stream batch data processing is preferred. Responsibilities: - Design and implement large-scale model training using distributed deep learning frameworks such as PyTorch, TensorFlow, Ray, etc., manage and optimize model training and inference processes, containerize using Docker, orchestrate and manage using Kubernetes and Kubeflow, and deploy and manage deep learning workloads on cloud platforms such as AWS, Google Cloud, Azure. -Application model compression and inference acceleration techniques, as well as stream batch data inference techniques. -Collaborate with the team to develop and execute technical strategies for distributed computing and deep learning solutions.