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 DL and HPC. 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 LLMs, computer aided engineering, quantum chemistry, autonomous vehicles, computer vision, and countless others. Did you know our team develops the GPU accelerated libraries and SDKs that help make these possible? In this role, you will work together with other developers on developing solutions that involve generalizations to sparse tensor computations, domain specific language (DSL) specifications of sparse storage formats, and on-demand code generation. Ideal candidates will not only have experience developing accelerated computing software, but also be motivated to advance the state-of-the-art in a variety of accelerated computing domains and DL frameworks like PyTorch. If this sounds exciting, we would love to meet you!