1 day ago
Base Salary
$123k - $184k/yr
Responsibilities
- Extend training or runtime machine learning frameworks and model-efficiency software tools with new features and optimizations.
- Assist with modeling, architecture, and development of machine learning hardware and co-designed software for inference and training.
- Develop optimized software such as machine learning kernels, compiler tools, and model-efficiency tools for AI models deployed on hardware.
- Apply machine learning techniques to products and AI solutions and collaborate with cross-functional teams.
- Develop, adapt, or prototype machine learning algorithms, models, and frameworks aligned with the product roadmap.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field is required.
- Master’s degree in Computer Science, Engineering, Information Systems, or a related field is preferred.
- Preferred qualifications include 1+ year of experience with machine learning frameworks, embedded-system development and optimization, machine-learning programming languages, statistics and probability, and work in a large matrixed organization.
- Preferred qualification includes 6+ months of experience with low-level interactions between operating systems and hardware.
- Preferred machine learning frameworks include TensorFlow, Caffe, Caffe2, PyTorch, and Keras.
- Preferred programming languages include Python, R, C, and C++.
Benefits
- Annual discretionary bonus program and potential annual RSU grants are offered in addition to base pay.
- Qualcomm provides a competitive benefits package supporting employees at work, at home, and at play.
- The role is posted with a location-specific annual pay range of $122,800.00 to $184,200.00.
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.