Senior GPU Supercomputer Scheduler Engineer

NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can take on, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Join us today!As a member of the GPU/HPC Infrastructure team, you will provide leadership in the design and implementation of groundbreaking GPU compute clusters that run demanding deep learning, high performance computing, and computationally intensive workloads. We seek a technology leader to identify architectural changes and/or completely new approaches for improving HPC schedulers for serving many simultaneous and large multi-node GPU workloads with many complex dependencies. This role offers you an excellent opportunity to deliver production grade solutions, get hands on with ground-breaking technology, and work closely with technical leaders solving some of the biggest challenges in machine learning, cloud computing, and system co-design.What you'll be doing:Design and develop enhancements to the HPC batch scheduler(s).Work extensively with HPC scheduler vendor on bug fixes and feature releasesProvide support to staff and end users to resolve batch scheduler issuesBuild and improve our ecosystem around GPU-accelerated computingPerformance analysis and optimizations of deep learning workflowsDevelop large scale automation solutionsRoot cause analysis and suggest corrective action for problems large and small scalesFinding and fixing problems before they occurWhat we need to see:Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience with 5+ years of work experienceStrong understanding of HPC batch schedulers, such as Slurm, RTDA or LSF and HPC workflows that use MPISignificant experience in Programming in C/C++ and advanced scripting in languages such as Python, Go, bash scriptingEstablished experience in Linux operating system, environment and toolsAccomplished in computer architecture and operating systemsDeep knowledge of Networking Protocols like InfiniBand, EthernetExperience analyzing and tuning performance for a variety of HPC workloadsIn-depth understating of container technologies like Docker, Singularity, PodmanFlexibility/adaptability for working in a dynamic environment with different frameworks and requirementsExcellent communication, interpersonal and customer collaboration skillsWays to stand out from the crowd:Knowledge in MPI and High-performance computingBackground in RDMA technologyExperience in kernel programmingOpen Source Software ContributorExperience with deep learning frameworks like PyTorch and TensorFlowPassionate about SW development processesWant to make what was impossible possible!The base salary range is 144,000 USD - 270,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.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.

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