GPU AI Compiler Engineer

Qualcomm•San Diego, CA

About The Position

Qualcomm Technologies, Inc. is seeking a GPU AI Compiler Engineer. This role involves applying knowledge of compilers to evaluate and improve the performance of different machine learning frameworks. The engineer will apply advanced graph optimization techniques to maximize GPU hardware resource utilization, write and review code for Machine Learning graph compilers and runtimes, and assist in identifying design deficiencies and developing solutions. Collaboration with team members to understand new features and functionality, and writing detailed design documentation are also key aspects of this position.

Requirements

Strong C/C++ programming skills
Familiarity with LLVM
Familiarity with a GPGPU API such as SYCL, CUDA or OpenCL.
Understanding of data structures and algorithms, including object-oriented programming
2+ years industry experience
Bachelor's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, Electrical Engineering, Game Rendering, or related work experience.
OR Master's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, Electrical Engineering, Game Rendering, or related work experience.
OR PhD in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, Electrical Engineering, Game Rendering, or related work experience.
1+ year of work experience with one or more programming language suitable for graphics (e.g., C++, C).

Nice To Haves

Knowledge of GPU architecture and optimization techniques for GPGPU code.
Experience with a Machine Learning Graph Compiler.
Knowledge of MLIR

Responsibilities

Applies knowledge of compilers to evaluate and improve performance of different machine learning frameworks.
Applies advanced graph optimization techniques to maximize utilization of GPU HW resources
Writes and reviews code for Machine Learning graph compilers and Machine Learning runtimes.
Assists in identifying deficiencies in designs and works with team members to develop solutions to improve designs.
Collaborates with team members to understand new features and functionality that align with needs and goals for implementation and customization.
Writes detailed design documentation and feature descriptions for projects.