We are looking for software engineers to contribute to the design and development of libraries and tools to simplify and accelerate computing for unstructured sparsity in deep learning and high‑performance computing. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations, using data centers powered by GPUs and high‑performance linear algebra libraries.
Applications of these technologies include large language models, computer‑aided engineering, quantum chemistry, autonomous vehicles, computer vision, and countless others. Our team develops the GPU‑accelerated libraries and SDKs that help make these possible.
What you will be doing:
- Design and develop a C++‑based system to simplify and accelerate computing for unstructured sparsity in deep learning and HPC on NVIDIA GPUs.
- Enable the system in languages and frameworks that are more commonly used in deep learning, such as Python and PyTorch.
- Evaluate and improve the performance of the system on real‑life applications.
- Realize opportunities to improve library quality, performance and maintainability by writing effective and well‑tested code for production use.
- Work closely with product management and other internal and external partners to understand feature and performance requirements and contribute to technical roadmaps.
What we need to see:
- BS, MS or PhD degree in Computer Science, Applied Math, or related field (or equivalent experience).
- 6+ years of overall experience in developing, debugging and optimizing high‑performance software using C++ and parallel programming; ideally for sparse linear algebra applications and using CUDA, MPI, OpenMP, or equivalent technologies.
- Experience with domain‑specific language design and compiler optimizations, in particular sparse compilers (MLIR or TACO).
- Excellent C++, Python, and CUDA programming skills.
- Strong collaboration, communication, and documentation habits and ideally experience with working in a globally distributed organization.
Ways to stand out from the crowd:
- Strong understanding of sparse computations, in particular sparsity in AI and HPC.
- Good understanding of large language models, deep learning methods and frameworks.
- Experience with low‑level GPU performance optimization.
- Understanding of numerical linear algebra methods such as direct and iterative solvers.
- Experience with adopting and advancing software development practices such as CI/CD systems and project management tools such as JIRA.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD – 287,500 USD for Level4, and 224,000 USD – 356,500 USD for Level5. You will also be eligible for equity and benefits.
NVIDIA is an equal‑opportunity employer and is committed to fostering a diverse work environment. We do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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