Key skills
C++CCUDA C/C++OpenMPMPIOpenSHMEMNVSHMEMParallel programmingParallel data structures and algorithmsCombinatoricsSparse representationsGPU kernel optimizationNsight SystemsNsight ComputeHigh-performance computingElectronic design automationComputational fluid dynamicsGraph analyticsMachine learningDeep learningAIMachine LearningDeep LearningAnalytics
About this role
NVIDIA is hiring a Senior Developer Technology Engineer for its Public Sector Developer Technology team. This role involves researching and developing techniques to GPU-accelerate applications in the federal ecosystem, collaborating with key developers, and optimizing core algorithms and data structures for performance on GPU architectures.
Responsibilities:
- Working directly with key application developers to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through reference code development, direct contribution to the full software stack including libraries, applications
- Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of architectures, software, and programming models, by investigating the impact on application performance and developer productivity
- Occasional travel from time to time for conferences and on-site visits with developers
Requirements:
- Have an MS or PhD degree or equivalent experience in Computer Science, Engineering or STEM field
- Programming fluency in C/C++ with a deep understanding of software design, programming techniques, and algorithms
- 5+ years of relevant work experience with parallel programming, ideally CUDA C/C++, OpenMP or MPI, or SHMEM (OpenSHMEM or NVSHMEM)
- Strong computer science fundamentals, ideally including parallel data structures and algorithms, combinatorics, and sparse representations
- Passion for optimizing codes to run exceptionally fast through parallel programming
- Experience optimizing complex codes, especially for GPUs, including kernel optimization and strong understanding of how software runs on hardware. A background with algorithm and architecture codesign is a plus
- Domain expertise in any of the following: electronic design automation, high-performance computing, computational fluid dynamics, data and graph analytics, data-science, network analysis, machine learning, or deep learning
- Experience in profiling and optimizing applications and frameworks including experience with Nsight Systems and Nsight Compute
- Experience in developing or optimizing workflows involving HPC and AI models