Senior Machine Learning Software Engineer

Qualcomm Technologies, Inc.

Engineering Group, Engineering Group >
Machine Learning Engineering

This individual independently plans, performs the moderately-defined responsibility for the designing, implementing and verification of software, typically C or C++ or Python, to enable audio, camera, graphics, video, sensors, wireless and other functionality for various operating systems running on ARM processors and other embedded HW like DSP processors, or GPU processors that are embedded into mobile, edge, auto and IOT products.

Responsibilities include integration, testing and performance optimization for embedded software subsystems, as well as the implementation of new tools. Other responsibilities include developing optimized software, such as ML kernels or tools like compilers, to make use of specific HW features; and/or working closely with HW teams for joint design/development. This individual may need to work with and/or optimize ML software frameworks like Tensor Flow or PyTorch to efficiently run ML algorithms on HW.

Coordinates dependencies with other teams, developing tools to improve the process, and assisting with the verification of the deliverables. Acts as a strong contributor at design reviews and project meetings.

Will accept a Master's Degree (or foreign academic equivalent) in Electrical Engineering, Computer Engineering, Computer Science or related degree field.

Pay Range: $ - $/year

Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.