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We are seeking an experienced HPC / CUDA Optimization Engineer with strong expertise in modern C++, CUDA, GPU computing, and performance optimization for large-scale scientific and engineering applications.
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 Oil & Gas domain is a huge bonus
- 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