HPC and CUDA Optimization Engineer

The team develops large-scale scientific and engineering applications and HPC and GPU-accelerated solutions.

• 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
• 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
• Provide technical leadership and guidance on GPU optimization, performance engineering, and software architecture
• Drive engineering best practices and contribute to technical decision-making for HPC and GPU-accelerated solutions

• 8+ 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
• Experience developing and optimizing performance-critical, high-load software systems
• Strong debugging and software architecture skills
• Proven ability to lead technical initiatives and collaborate effectively with cross-functional teams
• English proficiency at B2 level or higher
• Будет плюсом: hands-on experience with distributed and multi-GPU computing (MPI, NCCL, NVSHMEM), 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

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