For over 25 years, NVIDIA has pioneered visual and accelerated computing. Today, we're defining the future of AI, equipping millions with groundbreaking tools and essential training to lead a new era of innovation. Every month, NVIDIA’s training platform enables thousands of developers around the world to advance their AI skills and excel in their life’s work. We are seeking an innovative and experienced System Software Engineer to lead global training delivery operations. This foundational role is responsible for architecting, building, and scaling a world-class technical support function and the underlying systems for all Deep Learning Institute (DLI) users across the globe. You will be instrumental in building a stable, efficient, and scalable operation capable of handling massive growth.
Join a close-knit team where your contributions truly matter. As a core member of our learning systems platform team, you'll collaborate with subject matter experts to ensure our hands-on training sets the standard for user experience. You'll play a crucial role in making our purpose-built Learning Management System (LMS) platform a delightful and efficient tool that empowers both learners and instructors. Are you driven to build platforms that open the door to new careers? Do you thrive on creating systems that enable people to confidently apply advanced tools in their work? Want to be at the heart of making pivotal technologies like generative AI accessible and profoundly learnable for everyone? If so, let’s talk!
What you’ll be doing:
Architect, build, and evolve the scalable technology stack for global learner and instructor technical support.
Lead the global operationalization of support systems, to ensure high availability, performance, and efficient resource utilization.
Provide technical leadership and mentorship to a distributed operations team, driving excellence in the use of support technologies and processes.
Collaborate cross-functionally to translate support insights and user feedback into systemic improvements to shared NVIDIA services, the DLI platform, and overall experience for enterprises, learners, and instructors.
What we need to see:
Bachelor’s degree in Computer Science, a related technical field, or equivalent experience
Over 6 years of DevOps experience optimizing, deploying and running containerized applications (Docker, Kubernetes) across AWS, Azure, and GCP, including hands-on work with EKS, AKS, and GKE.
Proficient in Python and Linux shell scripting for automation, application development, system administration, and troubleshooting.
Validated experience architecting, implementing, and managing cloud infrastructure using Terraform.
Demonstrated ability as a meticulous problem-solver with strong analytical skills, capable of diagnosing and resolving complex technical challenges under pressure.
Excellent communication, teamwork, and collaboration skills, with an ability to articulate technical concepts clearly to diverse audiences and lead technical responses during incidents.
Ways to stand out from the crowd:
Proven experience designing and implementing event-driven architectures using pub/sub patterns with platforms like AWS SNS / SQS, Google Pub / Sub, or Azure Service Bus.
Knowledge of generative AI architectures (LLMs, diffusion models) and concepts such as Retrieval Augmented Generation (RAG) and vector databases.
Hands-on experience with the NVIDIA AI stack (NeMo, Triton Inference Server, TensorRT) for model development, serving, and optimization. Production experience with NVIDIA NIM is a strong plus.
Experienced in building and running CI/CD pipelines (Jenkins, GitLab CI) and managed software development environments, applying SRE principles to automate, enhance reliability, and improve performance.
Familiarity with Python-based Learning Management Systems (LMS) such as Open edX.
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers; we have some of the most forward-thinking and hardworking people in the world working for us and, due to unparalleled growth, our best-in-class teams are rapidly growing.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
