NVIDIA
Senior Accelerated Computing Architect
$184K–$356K
US, CA, Santa Clara · Senior · Full-time · Posted Apr 14, 2026
- Experience
- 6+ years of relevant work experience
- Education
- MS or Ph.D. in Computer Science, Computer Engineering, or Electrical Engineering, or equivalent experience
About the job
Analyzes and optimizes algorithms and applications for NVIDIA GPUs, collaborating across teams to guide accelerated-computing architecture and software-hardware co-design.
What you'll do
- Analyze and optimize performance on current or next-generation NVIDIA GPUs; create parallel algorithms, data structures, and reference code.
- Analyze interactions between hardware and software architectures and collaborate with hardware, software, product, and research teams.
- Explore applications for software-hardware co-design and communicate findings through publications and other materials.
What they ask for
- MS or Ph.D. in Computer Science, Computer Engineering, or Electrical Engineering, or equivalent experience.
- Strong mathematical fundamentals, including linear algebra and numerical methods.
- Hands-on experience with massively parallel GPU programming, such as CUDA or OpenCL.
- Strong knowledge of C and C++, including software design, programming techniques, and algorithms.
Nice to have
- Familiarity with MPI or OpenSHMEM/NVSHMEM, multicore CPU threading APIs, and Unix-style IPC APIs.
- Familiarity with Python.
Pay
184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)
Tools
NVIDIA GPUs, CUDA, OpenCL, MPI, OpenSHMEM/NVSHMEM, C, C++, Python
AI focus
NVIDIA uses AI tools in its recruiting processes; the job develops and optimizes computing for machine learning and AI applications.
Model-written summary · the original posting is authoritative