Deep Learning Compiler Engineer - CUDA
Work on the design and implementation of a tile-aware GPU programming model: its DSL and core compiler, with a focus on performance for emerging GPU architectures. The role sits in NVIDIA's Architecture group, which develops parallel programming models, compiler infrastructure, and architecture features to maximize GPU performance.
The engineer will analyze AI/LLM workloads, iterate on compiler architecture, and propose compiler- and DSL-level solutions for next-generation GPUs.
Entry-level. The posting requests 2+ years of relevant work experience.
Primary engineering and architecture tasks for the compiler and programming model:
Core technical requirements and preferred skills.
Master's or PhD in Computer Engineering, Computer Science & Engineering, Computer Science, AI, or equivalent practical experience. Equivalent practical experience in related technical fields is acceptable.
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
