Senior Lab Infrastructure and Automation Manager

Be part of NVIDIA's Education Services division as an Lab Infrastructure & Automation Manager in charge of developing, overseeing, and ground-breaking our innovative lab environments. This position plays a crucial role in rapidly growing and assisting our practical training programs for in-house trainers and Authorized Learning Partners (ALPs) in various time zones worldwide

What You’ll Be Doing

• Oversee setup, integration, and maintenance across two physical labs, internal and external cloud platforms, ensuring systems are updated and reliable during workshop delivery.
• Compose and scale virtualization solutions that support ALPs, collaborating closely with course developers to develop and refine lab scripts and hands-on exercises.
• Provide live technical support to NVIDIA Academy trainers and ALPs during and after workshops, ensuring smooth operations across all time zones.
• Develop mechanisms for integrating technical lab environments with the Learning Management System (LMS), automating workflows for users accessing from multiple platforms, as well as for workshop administrators
• Lead operational processes—including lab scheduling, fixing, and test deliveries—to boost workshop quality and increase trainer/developer efficiency.
• Serve as a key point of contact for cross-geo workshop support.
  
  

• Bachelor’s degree in computer science, engineering, or related field, or equivalent experience.
• 5 years of experience managing data center or cloud infrastructure
• Strong proficiency in Linux, virtualization, lab networking, and integration of lab automation tools (e.g., Kubernetes, Docker, Ansible, Git).
• Proficient in fixing problems efficiently, adept at resolving issues promptly.
• Moderate python coding skills
• Strong verbal and written English interpersonal skills.
  
  

• Practical experience with NVIDIA GPUs, networking, and software solutions.
• Experience in designing and supporting labs for virtual, cloud-based, or hybrid training platforms, including integration with automation and orchestration tools.
• Hands-on experience working with AWS, GCP, Azure, or OCI environments in a lab or training context.
• Possession of relevant certifications such as CCNP, RHCSA, Certified Kubernetes Administrator, or equivalent credentials.