1 day ago
Base Salary
$162k - $243k/yr
Responsibilities
- Extend training or runtime frameworks and model-efficiency software tools with new features and optimizations.
- Model, architect, and develop machine learning hardware co-designed with machine learning software for inference or training.
- Develop optimized machine learning kernels, compiler tools, and model-efficiency tools that enable AI models to use hardware features.
- Develop, adapt, and prototype machine learning techniques and solutions for complex products and AI applications.
- Conduct experiments to train and evaluate machine learning models and software.
- Collaborate with hardware teams and provide guidance to other team members.
Requirements
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field and 4+ years of related engineering experience; alternatively, a master's degree and 3+ years or a PhD and 2+ years.
- Preferred master's degree in a relevant field.
- Preferred 5+ years of experience with machine learning frameworks, embedded system development and optimization, and machine-learning programming languages.
- Preferred 5+ years of experience using statistics and probability.
- Preferred 3+ years of experience in a large matrixed organization.
- Preferred 2+ years of experience with low-level interactions between operating systems and hardware.
- Preferred experience in technical leadership and interaction with senior leadership.
Benefits
- Annual discretionary bonus program and opportunity for annual RSU grants.
- Competitive benefits package supporting employees at work, at home, and at play.
- Annual pay range is $162,000.00–$243,000.00 for the posted location.
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.