Description
No description provided.
Responsibilities
•Design, develop, and optimize CUDA kernels for large-scale scientific and engineering applications
•Analyze and improve GPU performance using profiling tools to identify and resolve bottlenecks
•Implement and optimize distributed and multi-GPU computing solutions using MPI, NCCL, and NVSHMEM
•Develop and maintain high-performance C++ and Python code for performance-critical, high-load systems
•Collaborate with cross-functional teams to architect scalable and efficient software solutions
•Debug complex performance and memory issues across GPU architectures and distributed systems
•Research and apply best practices in HPC, numerical methods, and GPU computing to improve existing codebases
Requirements
•5+ years of professional experience with C++ and Python development
•Deep knowledge of CUDA, GPU architecture, PTX, memory hierarchy, and kernel optimization
•Experience with GPU profiling, performance analysis, and bottleneck identification
•Hands-on experience with distributed and multi-GPU computing (MPI, NCCL, NVSHMEM)
•Experience developing and optimizing performance-critical, high-load software systems
•Strong debugging and software architecture skills
Nice to have
•Knowledge of the Oil & Gas domain
•Experience with RTM/FWI, seismic imaging, or geoscience applications
•Development of HDF5-based data viewing and analysis tools
•Familiarity with scientific computing and numerical methods
Conditions
No conditions specified in the posting.
