Machine Learning Researcher, Senior

Qualcomm•San Diego, CA

3d•$159,100 - $238,700

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 Researcher, you will conduct fundamental research that creates innovative machine learning methodology that achieves beyond state-of-the-art performance. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning research.

Requirements

Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.
6+ months of academic and/or work experience developing and/or optimizing machine learning models, systems, platforms, or methods.

Nice To Haves

PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.
2+ publications at a machine learning conference.
2+ years of experience working in a large matrixed organization.
1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).
1+ year experience with machine learning research related to new models, systems innovations, platforms, or methodology.

Responsibilities

Applies Machine Learning knowledge to conduct fundamental research to create new models or training methods in various technology areas (e.g., deep generative models, Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning, unsupervised learning, and graph NNs).
Drives systems innovations for model efficiency advancement on device as well as in the cloud, including auto-ML methods for the creation and optimization of efficient models (e.g., model compression, quantization, architecture search, and kernel/graph compiler/scheduling).
Performs platform research to enable new machine learning compute paradigm (e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, and quantum machine learning).
Develops and publishes research findings in the form of presentations and conference papers.
Conducts research on machine learning and develops innovative or patentable ideas for new solutions.
Develops, tests, optimizes, and documents complex new or updated machine learning algorithms, models, and methods that are aligned with research strategies.