Senior HPC Applications Engineer

NVIDIA is building a next-generation hybrid computing environment that merges large-scale HPC GPU clusters with quantum computing platforms. As a Senior HPC Applications Engineer, you will collaborate with researchers and engineers to optimize and ensure efficient execution of advanced simulation and AI-driven applications on this hybrid platform. Responsibilities • Collaborate with quantum and domain scientists to install, configure, compile, and optimize research applications on the HPC + quantum environment • Profile and tune performance for GPU-accelerated and hybrid workloads using tools such as NVIDIA Nsight, nvprof, and CUDA-Q profilers • Optimize job execution and resource utilization via Slurm policies, GPU partitioning, and hybrid orchestration between classical and quantum nodes • Develop and maintain containerized environments (Singularity, Kubernetes, or Docker) to ensure reproducible builds and easy deployment • Advise researchers on parallelization strategies, CUDA kernels, MPI configurations, and scaling behaviors • Work with system engineers to validate firmware, driver, and library configurations that maximize application performance (e.g., CUDA, cuQuantum, cuBLAS, NCCL) • Integrate quantum SDKs and simulators (e.g., CUDA-Q, Qiskit, or IonQ/QuEra APIs) into HPC workflows • Establish performance baselines and benchmarking suites for GPU and hybrid workloads; publish metrics and dashboards • Support and train users — from onboarding and code migration to advanced performance debugging. Customer first focus • Contribute to architecture evolution by providing feedback on workload patterns, bottlenecks, and future capacity planning Skills • 12+ years of experience in HPC application performance engineering, computational science, or scientific software development • Strong background in GPU programming (CUDA, cuQuantum, CUDA-Q) and parallel programming (MPI, OpenMP) • Proficiency with Linux, Slurm, containerization, and CI/CD pipelines (GitHub, Jenkins, Ansible, or GitLab CI) • Experience in profiling, benchmarking, monitoring, and optimizing scientific or AI/ML applications on multi-GPU systems • Working knowledge of NVIDIA HPC SDK, CUDA-Q, or cuQuantum stack • Bachelor's or Master's degree (or equivalent experience) in Computer Science, Physics, Applied Mathematics, or Engineering (PhD a plus) • Excellent communication and collaboration skills to support a multidisciplinary research community • Exposure to other quantum computing frameworks • Experience optimizing multi-physics, molecular dynamics, or quantum chemistry codes • Demonstrated expertise in GPU-accelerated AI/ML model training and integration with scientific codes • Familiarity with hybrid workflow orchestration — combining HPC scheduling, quantum job APIs, and data movement pipelines • Contribution to open-source HPC or quantum software projects Benefits • Equity • Benefits Company Overview • NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. It was founded in 1993, and is headquartered in Santa Clara, California, USA, with a workforce of 10001+ employees. Its website is https://www.nvidia.com. Company H1B Sponsorship • NVIDIA has a track record of offering H1B sponsorships, with 1418 in 2025, 1356 in 2024, 976 in 2023, 835 in 2022, 601 in 2021, 529 in 2020. Please note that this does not guarantee sponsorship for this specific role.