Nvidia Deep Learning Compiler Engineer - MLIR 

United States, Texas 

639981960

What you'll be doing:

In this role, you will be responsible for analyzing deep learning networks and developing compiler optimization algorithms. You’ll collaborate with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. The scope of these efforts includes defining public APIs, performance tuning and analysis, crafting and implementing compiler and optimization techniques for neural networks, and other general software engineering work.

What we need to see:

• Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience)

• 3+ years of relevant work or research experience in performance analysis and compiler optimizations.

• Ability to work independently, define project goals and scope, and lead your own development effort.

• Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.

• Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.

Ways to stand out from the crowd:

• Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience.

• Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, deep learning models and algorithms, and deep learning framework design.

• A history of mentoring junior engineers and interns is a bonus.