Senior Math Libraries Engineer, CPU and GPU Optimization at NVIDIA

What you'll be doing:

• Design modern, flexible, and easy to use APIs and kernels for math libraries and lead design reviews with all collaborators.
• Work closely with internal (e.g., Engineering, Product Management) and external partners such as researchers to understand their use cases and requirements.
• Work with internal and external customers to deliver timely math libraries releases. 
• Become a domain expert by continuously surveying current trends in software systems.

What we need to see:

• PhD or MSc degree in Computer Science, Applied Math, or a related science or engineering field is preferred (or equivalent experience).
• 12+ years of experience designing and developing software for high-performance computing and/or AI applications.
• Advanced C++ skills, including modern design paradigms (e.g., template meta-programming, RAII).
• Parallel programming experience with CUDA, OpenCL or vector programming on CPU (AVX, NEON or similar).
• Strong collaboration, communication, and documentation habits.
• Experience with ARM, RISC-V and/or x86_64 CPU architectures.

Ways to stand out from the crowd:

• Strong background in numerical methods (e.g., FFT, numerical linear algebra).
• Programming skills with Python, and modern automation setups for both building software (e.g. cmake) as well as testing it (e.g. CI/CD, sanitizers).
• Background with cross-compilation, setting up CPU/GPU/accelerator (cross-)compilation toolchains and bringing existing codes to new architectures.
• Experience with CCCL, OpenMP, OpenACC, multi-threading, MPI, PGAS.
• Experience with scientific and deep learning libraries and frameworks such as PyTorch, JAX, MKL, MAGMA, PETSc, Kokkos, etc.