Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Algorithms @ 4
Data Structures @ 4
Machine Learning @ 4
Data Science @ 4
Hiring @ 4
Graph Theory @ 4
Parallel Programming @ 6
CUDA @ 6
GPU @ 4
Deep Learning @ 4
AI @ 4
Profiling @ 4
HPC @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is hiring a Senior Developer Technology Engineer for the Public Sector Developer Technology (DevTech) team to research and develop techniques to GPU-accelerate leading applications in the federal ecosystem. Target application areas include computational fluid dynamics (CFD), electronic design automation (EDA), graph theory/analytics, weather/climate modeling, and AI in HPC. The role focuses on in-depth analysis and optimization to achieve best possible performance on current and next-generation GPU architectures.
Responsibilities
- Work directly with key application developers to understand current and future problems and craft/optimize core parallel algorithms and data structures for GPUs.
- Develop reference code and directly contribute across the software stack, including libraries and applications.
- Collaborate closely with NVIDIA architecture, research, libraries, tools, and system software teams to influence architecture, software, and programming model design by investigating impacts on application performance and developer productivity.
- Occasional travel for conferences and on-site visits with developers.
Requirements
- MS or PhD degree (or equivalent experience) in Computer Science, Engineering, or a 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 experience with CUDA C/C++, OpenMP, 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.
Preferred / Ways to stand out
- Experience optimizing complex codes for GPUs, including kernel optimization and a strong understanding of how software runs on hardware; background with algorithm and architecture codesign is a plus.
- Domain expertise in one or more of: electronic design automation, high-performance computing, computational fluid dynamics, data and graph analytics, data science, network analysis, machine learning, or deep learning.
- Experience profiling and optimizing applications and frameworks, including Nsight Systems and Nsight Compute.
- Experience developing or optimizing workflows involving HPC and AI models.
Compensation & Benefits
- Base salary ranges provided by location and level:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- Eligible for equity and benefits (link provided in original posting).
Additional information
- Hybrid role indicator: #LI-Hybrid.
- Application acceptance at least until April 13, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and provides a diverse work environment.