The company is seeking a passionate, world-class computer scientist and engineer to accelerate energy simulation and AI workflows on its platforms. The focus will be on CUDA performance optimization for workloads including seismic processing and reservoir simulation, along with related HPC/AI production workflows. You will engage hands-on with customer and partner engineering teams, as well as the company's product and engineering groups, to drive measurable speedups and scalable performance on multi-GPU and multi-node systems.
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Responsibilities
- Profile, analyze, and optimize GPU-accelerated applications with emphasis on CUDA kernels, memory movement, concurrency, and end-to-end throughput.
- Drive performance improvements across the stack, including:
- CUDA C++ kernel optimization, launch configuration, memory hierarchy, streams/events.
- GPU libraries (as applicable): cuBLAS, cuFFT, cuSPARSE, cuSOLVER, NCCL.
- Multi-GPU and multi-node scaling using MPI + NCCL, CPU/GPU overlap, communication patterns.
- Develop and maintain reference implementations, examples, and/or patches to customer code to enhance performance and portability.
- Support customer engagements (from proofs of concept to production), addressing correctness/performance issues and advising on best practices for deployment.
- Collaborate with internal teams to file actionable issues, validate fixes, and influence the roadmap based on customer requirements in the Energy sector.
Requirements
- BS/MS (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Physics, Applied Mathematics, or a related field.
- Strong programming skills in C/C++ and Python on Linux.
- Hands-on experience with CUDA programming and GPU performance optimization concepts.
- Proficient in profiling and debugging performance using tools like NVIDIA Nsight Systems / Nsight Compute (or equivalent).
- Solid understanding of parallel computing and performance fundamentals (including vectorization, threading, NUMA, memory bandwidth/latency).
- 5+ years of relevant experience in GPU/HPC optimization with a proven track record of achieving speedups and scaling improvements.
Location
Switzerland, Zurich
