M/L Compiler Engineer

Qualcomm•New York, NY

About The Position

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.

Nice To Haves

Master's degree in Computer Science, Engineering, Information Systems, or related field.
2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
2+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++)
2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
2+ years experience working in a large matrixed organization.
1+ year of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).

Responsibilities

Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions.
Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development.
Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.
Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers.
Conducts complex experiments to train and evaluate machine learning models and/or software independently.