Senior Deep Learning Compiler Engineer

Analyzing deep learning networks and developing compiler optimization algorithms.

Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.

Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.

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 efforts.

Excellent C/C++ and Python 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.

Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.

Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.

Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.

GPU kernel generation with high performance and fast build time.

A track record of success in mentoring junior engineers and interns is a bonus.