Senior Math Libraries Engineer - Sparsity in AI
$184k - $357k • Remote • US, CA, Santa Clara
Posted 1d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
We are seeking software engineers to design and develop libraries and tools that simplify and accelerate computing for unstructured sparsity in Deep Learning (DL) and High-Performance Computing (HPC). Our team develops GPU-accelerated libraries and SDKs that are crucial for AI, data analytics, and scientific simulations. In this role, you will contribute to solutions involving sparse tensor computations, domain-specific language (DSL) specifications for sparse storage formats, and on-demand code generation. The ideal candidate will have experience in accelerated computing software development and a passion for advancing the state-of-the-art in various accelerated computing domains and DL frameworks like PyTorch.
Responsibilities
- Design and develop a C++-based system to simplify and accelerate computing for unstructured sparsity in DL and HPC on NVIDIA GPUs.
- Enable the system in languages and frameworks commonly used in DL, such as Python and PyTorch.
- Evaluate and improve the system's performance on real-life applications.
- Write effective, well-tested code for production use to improve library quality, performance, and maintainability.
- Collaborate with product management and partners to understand feature and performance requirements and contribute to technical roadmaps.
Requirements
- BS, MS, or PhD degree in Computer Science, Applied Math, or related field (or equivalent experience).
- 6+ years of experience in developing, debugging, and optimizing high-performance software using C++ and parallel programming.
- Experience with sparse linear algebra applications and technologies like CUDA, MPI, or OpenMP.
- Experience with domain-specific language design and compiler optimizations, particularly sparse compilers (MLIR or TACO).
- Excellent C++, Python, and CUDA programming skills.
- Strong collaboration, communication, and documentation habits.
Benefits
- Equity
- Benefits