Nvidia Senior HPC Applications Engineer 

United States, Texas 

789919730

We are building anext-generationmultiple quantumcomputing platforms. As our HPC Application Engineer, you’ll work at the intersection of scientificresearch, high-performancerun efficiently,reliably, and scalably on this new hybrid quantum-classical platform. You’ll partner closely with quantum researchers, software developers, and system engineers to deploy, profile, and tune applications that leverage both GPU acceleration and quantum backends.

What You’ll Be Doing:

• Collaborate with quantum and domain scientiststo install, configure, compile, and optimize research applications on the HPC + quantum environment.

• Profile and tune performancefor GPU-accelerated and hybrid workloads using tools such as NVIDIA Nsight, nvprof, and CUDA-Q profilers.

• Optimize job execution and resource utilizationvia 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 engineersto 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 suitesfor 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 evolutionby providing feedback on workload patterns, bottlenecks, and future capacity planning.

What We Need to See:

• 12+ years of experience inHPC application performance engineering,computational science, orscientific software development.

• Strong background inGPU programming (CUDA, cuQuantum, CUDA-Q)andparallel programming (MPI, OpenMP).

• Proficiency withLinux,Slurm,containerization, andCI/CD pipelines(GitHub, Jenkins, Ansible, or GitLab CI).

• Experience inprofiling, benchmarking, monitoring, and optimizingscientific or AI/ML applications on multi-GPU systems.

• Working knowledge ofNVIDIA HPC SDK,CUDA-Q, orcuQuantumstack.

• 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.

Ways to Stand Out from the crowd:

• Exposure to otherquantum computing frameworks.

• Experience optimizingmulti-physics, molecular dynamics, or quantum chemistrycodes.

• Demonstrated expertise inGPU-accelerated AI/ML model trainingand integration with scientific codes.

• Familiarity withhybrid workflow orchestration— combining HPC scheduling, quantum job APIs, and data movement pipelines.

• Contribution toopen-source HPC or quantum softwareprojects.

This role is critical to unlocking the full potential of our hybrid quantum-HPC architecture. You’ll empower researchers to explore new frontiers in quantum design, life sciences, and AI-driven discovery — ensuring that every computation, classical or quantum, runs at its highest efficiency.