Qualcomm Machine Learning Researcher 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
- 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.
- PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.
- 10+ years experience with machine learning research related to new models, systems innovations, platforms, or methodology.
- 2+ publications at a machine learning conference.
- 2+ years managing operating budgets and/or project financials.
Responsibilities
- Leverages expert Machine Learning knowledge to influence and oversee the 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).
- Directs and oversees 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).
- Determines guidelines for performing 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.
- Partners with senior stakeholders across the business to create the strategy for research programs across multiple technologies or products related to machine learning and executes on research proposals of various levels of complexity.
- Drives innovation in ideas and solutions based on current and future industry trends.
- Sets strategies to develop, test, optimize, and document new or updated machine learning algorithms, models, and methods.
Other
- Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 10+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- 4+ years in a technical leadership role with or without direct reports (only applies to positions with direct reports).
- 4+ years of experience working in a large matrixed organization.
- 3+ years of work experience in a role requiring interaction with executive leadership (e.g., Vice President and above).
