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What you will be doing:
crafting and developing Python APIs for math libraries (e.g., linear algebra),
prototyping integrations of developed APIs into targeted libraries and frameworks,
conducting performance analysis and benchmarking, performance tuning and optimization, of numerical software on various CPU and GPU architectures,
working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of NVIDIA math libraries,
finding opportunities to improve target user experiences.
see:
PhD or MSc degree in Computer Science, Applied Math, or related science or engineering field is preferred or equivalent experience.
Excellent Python and C++ programming and software design skills, including functional and performance tests design.
Experience developing Python APIs in pythonic style
Experience using one or more of Numpy, CuPy, SciPy, JAX, PyTorch, TensorFlow, Numba.
3+ years experience developing, debugging, and optimizing high-performance applications on parallel computing platforms.
Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning.
Proven experience in working on software development projects in an agile environment.
Strong collaboration, communication, and documentation habits.
Ways to stand out from the crowd:
Parallel programming experience with GPUs (CUDA or OpenCL), multi-threading, or MPI.
Good knowledge of CPU and/or GPU hardware architecture.
You will also be eligible for equity and .
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