NVIDIA is hiring a Senior HPC Applications Engineer

NVIDIA is looking for a Senior HPC Applications Engineer to ensure advanced simulation, optimization, and AI-driven applications run efficiently, reliably, and scalably on a hybrid quantum-classical platform. You'll work at the intersection of scientific research, high-performance computing, and quantum technologies, partnering with quantum researchers, software developers, and system engineers.

What You'll Do

• Collaborate with quantum and domain scientists to install, configure, compile, and optimize research applications on the HPC and 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.
• Contribute to architecture evolution by providing feedback on workload patterns, bottlenecks, and future capacity planning.

What We're Looking For

• 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.
• Excellent communication and collaboration skills to support a multidisciplinary research community.

Nice to Have

• 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.
• PhD a plus.

Technical Stack

• CUDA, cuQuantum, CUDA-Q, MPI, OpenMP
• Linux, Slurm
• Singularity, Kubernetes, Docker
• NVIDIA Nsight, nvprof
• GitHub, Jenkins, Ansible, GitLab CI
• NVIDIA HPC SDK, cuBLAS, NCCL
• Qiskit, IonQ/QuEra APIs

Team & Environment

You will partner with quantum researchers, software developers, and system engineers.

Benefits & Compensation

• Compensation: $224,000 USD - $356,500 USD for Level 5, and $272,000 USD - $425,500 USD for Level 6.
• Equity eligible.
• Comprehensive benefits package.

Work Mode

This role operates on a hybrid work mode.

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.