NVIDIA
Senior Accelerated Computing Architect
$184K–$356K
US, CA, Santa Clara · Senior · Full-time · Posted May 7, 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
Optimizes GPU performance and develops parallel algorithms and software-hardware co-design solutions for accelerated computing applications.
What you'll do
- Analyze and optimize performance on current and next-generation NVIDIA GPUs; benchmark and profile GPU and CPU cluster workloads.
- Create and optimize parallel algorithms, data structures, and reference code, and analyze hardware-software interactions.
- Collaborate across hardware, software, product, and research teams; communicate work through publications and other technical 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++.
- Experience benchmarking, profiling, and characterizing workloads on GPU and CPU clusters.
Nice to have
- Familiarity with multi-node communication APIs such as 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; 224,000 USD - 356,500 USD base salary
Tools
NVIDIA GPUs, CUDA, OpenCL, MPI, OpenSHMEM/NVSHMEM, C, C++, Python
AI focus
The role supports machine learning and AI computing applications. NVIDIA also states that it uses AI tools in its recruiting processes.
Model-written summary · the original posting is authoritative