NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA reinvented itself over two decades, inventing the GPU in 1999 and revolutionizing computer graphics. Design and implement GPU compute clusters for deep learning and high-performance computing. - Provide leadership and strategic mentorship on the management of large-scale HPC systems including the deployment of compute, networking, and storage. - Develop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions. - Build and nurture customer and cross-team relationships to consistently support the clusters and address changing user needs. - Support our researchers to run their workloads including performance analysis and optimizations. - Conduct root cause analysis and suggest corrective action. Proactively find and fix issues before they occur. - Build innovative tooling to accelerate researchers' velocity, troubleshooting, and software performance at scale. - Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience. - Minimum of 6 years of experience crafting and operating large scale compute infrastructure. - Experience with AI/HPC job schedulers and orchestrators, such as Slurm, K8s or LSF. Applied experience with AI/HPC workflows that use MPI and NCCL. - Proficient in using Linux including Centos/RHEL and/or Ubuntu Linux distributions. A solid understanding of container technologies like Enroot, Docker and Podman. - Proficiency in one scripting language (Python, Bash) and at least one compiled language (Golang, Rust, C, C++...). - Experience analyzing and tuning performance for a variety of AI/HPC workloads. Excellent problem-solving to analyze complex systems, identify bottlenecks, and implement scalable solutions. - Excellent communication and teamwork skills, with the ability to work effectively with diverse teams and individuals. - Passion for continual learning and staying ahead of new technologies and effective approaches in the HPC and AI/ML infrastructure fields. - Experience with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking. - Experience with Machine Learning and Deep Learning concepts, algorithms and models. - Familiarity with High-Speed Networking pertaining to HPC including InfiniBand, RDMA, RoCE and Amazon EFA. - Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workload. Experience working with deep learning frameworks including PyTorch, MegatronLM and TensorFlow. - Familiarity with metrics collection and visualization at scale with Prometheus, OpenSearch and Grafana. NVIDIA offers competitive salaries and benefits. Our experienced and talented employees contribute to our outstanding engineering team's rapid growth. If you're a tech enthusiast, apply now! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 3, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.