Senior Software Engineer, MathDx – cuBLASDx and cuSolverDx

Job Description

<p><h3>Overview</h3>
<p>Why consider this job opportunity:</p>
<ul>
<li>Competitive salary and a generous benefits package</li>
<li>Opportunity for career advancement and growth within the organization</li>
<li>Work with some of the most forward-thinking and hardworking professionals in the industry</li>
<li>Contribute to groundbreaking projects in high-performance computing and AI</li>
<li>Chance to design and optimize cutting-edge mathematical libraries for diverse applications</li>
</ul>
<h3>Responsibilities</h3>
<ul>
<li>Design modern, flexible, and easy-to-use APIs for math libraries and lead design reviews with collaborators</li>
<li>Collaborate closely with internal teams and external partners to understand use cases and requirements</li>
<li>Become a domain expert by continuously surveying current trends in software systems</li>
<li>Develop and optimize math libraries for high-performance computing and AI applications</li>
<li>Engage in code reviews and documentation to ensure quality and clarity in development processes</li>
</ul>
<h3>Qualifications</h3> <ul>
<li>PhD or MSc degree in Computer Science, Applied Math, or a related science or engineering field (or equivalent experience)</li>
<li>3+ years of experience designing and developing software for high-performance computing and/or AI applications</li>
<li>Advanced C++ skills, including modern design paradigms (e.g., template meta-programming, RAII)</li>
<li>Parallel programming experience with CUDA or OpenCL</li>
<li>Strong collaboration, communication, and documentation habits</li>
</ul>
<h3>Preferred Qualifications</h3>
<ul>
<li>Experience using graph compilers and/or Just In Time compilation workflows (e.g., XLA, LLVM, MLIR, Numba, NVRTC)</li>
<li>Programming skills with Python and modern automation setups for software building and testing (e.g., cmake, CI/CD)</li>
<li>Experience with CCCL, OpenMP, OpenACC, multi-threading, MPI, PGAS</li>
<li>Strong background in numerical methods (e.g., FFT, numerical linear algebra)</li>
<li>Familiarity with scientific and deep learning libraries and frameworks such as PyTorch, JAX, MKL, MAGMA, PETSc, Kokkos, etc.</li>
</ul>
<p>#SoftwareEngineering #HighPerformanceComputing #AI #CareerGrowth #CompetitiveBenefits #InnovationInTech</p>
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