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S&P GlobalCloud & Application Security Engineer
Cloud & Application Security Engineer building security - first culture across the firm. Working with development and operations teams to remediate vulnerabilities and drive security practices.
About the role
- 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.
- Contribution to architecture evolution by providing feedback on workload patterns, bottlenecks, and future capacity planning.
Requirements
- 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.
Benefits
- equity
- benefits
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