Join Deloitte's Technology & Transformation practice, where you'll leverage vast data resources to drive strategic guidance and implementation services. We help companies manage data, transform it into actionable insights, and gain a competitive edge.

Our practice encompasses business intelligence, data management, performance management, and cutting-edge analytics including big data, cloud, cognitive computing, and machine learning.

Key responsibilities involve designing robust GPU landing zones, selecting optimal NVIDIA GPU instances for various AI workloads, and engineering cloud GPU clusters with advanced orchestration. You will develop strategies for high-throughput storage, build hybrid connectivity, and implement Infrastructure as Code for efficient deployments.

Further duties include integrating cloud ML services, establishing comprehensive observability for GPU performance and cost, and managing AI infrastructure FinOps. This role requires hands-on experience with cloud GPU capacity, high-performance networking, and managed Kubernetes/HPC environments.

We are seeking candidates with 2-12 years of experience in infrastructure, SRE, HPC, or platform engineering, with a strong background in GPU or accelerated-computing environments. Essential skills include proficiency in NVIDIA GPU architecture, cluster design, Kubernetes/OpenShift or Slurm, and a solid understanding of Linux, containers, and the CUDA ecosystem.

Candidates should possess deep expertise in at least one major cloud platform (AWS, Azure, GCP) and experience with Infrastructure as Code, CI/CD, and GitOps. A solid grasp of AI workloads and production AI infrastructure operations, including security and resilience, is crucial for success in this role.