Description
We are looking for an AI & Deep Learning Compiler Engineer to join our Deep Learning & AI Compiler (DLC) team. As a member of this team, you will be responsible for analyzing deep learning networks and developing compiler optimization algorithms. You will collaborate with members of the deep learning software framework teams and the GPU architecture teams to accelerate the next generation of deep learning software.
Our DLC has been the backbone of NVIDIA's inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Time and Just-in-Time.
Some of the key responsibilities of this role include:
Analyzing deep learning networks and developing compiler optimization algorithms. Collaborating with members of the deep learning software framework teams and the GPU architecture teams to accelerate the next generation of deep learning software. Defining public APIs, performance optimizations and analysis, crafting and implementing compiler techniques for AI workloads and future NVIDIA GPUs.
To be successful in this role, you will need to have a strong background in computer science, computer engineering, or a related field, with a focus on performance analysis and compiler optimizations. You should have experience with compiler technologies such as MLIR, LLVM, XLA, Triton, and excellent C/C++ and Python programming and software design skills.
Additionally, you should be able to work independently, define project goals and scope, and lead your own development efforts. Strong interpersonal skills are required, along with the ability to work in a dynamic product-oriented team.
Some of the preferred qualifications for this role include:
Proficiency in CPU and/or GPU architecture. CUDA or OpenCL programming experience. Understanding of deep learning models, algorithms and frameworks, such as PyTorch, JAX. GPU kernel authoring and performance analysis using tools such as Nsight Compute. A track record of success in mentoring early-career engineers and interns is a bonus. Track record on new hardware bring-up is a plus.
If you are a creative and autonomous engineer with a real passion for technology, we want to hear from you. You will also be eligible for equity and benefits.