Position Overview: The ideal candidate should have a strong background in parallel computing and performance optimization using CUDA.
Responsibilities:
- Identify and resolve performance issues and bugs related to CUDA usage.
- Analyze and improve algorithm performance through efficient parallelization.
- Stay updated with new technologies and best practices in CUDA and parallel computing.
Required Qualifications:
- Bachelor s degree in Computer Science Computer Engineering or related fields.
- Minimum of 5 years of software development experience with at least 2 years specifically in CUDA development.
- Ability to solve complex problems and work both independently and in a team.
- Good communication skills and ability to work in a collaborative environment.
Knowledge and Skills:
- Proficiency in C/C.
- Experience with code optimization for performance and efficient resource usage.
- Experience with CUDA version 12.0 or above (12.3 preferred).
- Knowledge of frameworks and libraries like cuBLAS and cuDNN.
- CUDA Performance Optimization.
performance optimization,cuda,code optimization,c++,cublas,parallel computing,algorithm performance,c,cudnn,c/c++