Engineering Group, Engineering Group > Machine Learning Engineering
Creates advanced machine learning techniques that enable a broad set of technology verticals or designs and extends training or runtime frameworks or model efficiency software tools with new features and optimizations. Models, architects, and develops advanced machine learning hardware (co-designed with machine learning software) for inference or training solutions. These enable the discovery and improvement of state-of-the-art machine learning solutions that has general applicability at functional platform level towards audio, camera, graphics, video, sensors, wireless, and other functionality over various operating systems running on ARM processors and other embedded hardware like DSP/NSP processors, GPU processors that are embedded into mobile, edge, auto, and IOT products, or on data center based systems such as GPUs or dedicated AI hardware. Develops optimized software to enable AI models efficiently deployed on hardware, such as machine learning kernels, compiler tools, or model efficiency tools, to make sure of specific hardware features, and/or working closely with hardware teams for joint design and development. Works with and/or optimize machine learning software frameworks like TensorFlow or PyTorch to efficiently run machine learning algorithms on hardware.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
Qualcomm's Multimedia R&D and Standards Group is seeking passionate candidates with expertise in Computer Vision or Computer Graphics. The team is developing advanced AI and deep learning algorithms, architectures, and systems for applications enriching the embedded systems for Smartphone and Extended Reality.
The candidate should bring a deep understanding in computer vision or computer graphics, exhibiting excellent analytical and algorithm development skills and proficiency in Python, C/C++ or OpenGL programming. The selected candidate will have responsibilities in one or more of the following areas:
Must have Qualifications
Bachelors - Computer Science, Bachelors - Engineering, Bachelors - Information Systems
2+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Masters - Computer Science, Masters - Engineering, Masters - Information Systems
2+ years’ experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++). ,1+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware ,2+ years’ experience using statistics and probability (e.g., conditional probability, Bayes rule) ,2+ years’ experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media). ,2+ years’ experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras) ,1+ years of work experience in a role requiring interaction with senior leadership (e.g., Director level and above). ,2+ years of experience working in a large matrixed organization.
AI Frameworks, Calculus, Data Manipulation, Deep Learning, Computer Vision, Computer Graphics, Machine Learning, Performance Optimization, Python, Statistics.
All Qualcomm employees are expected to actively support diversity on their teams, and in the Company.
Although this role has some expected minor physical activity, this should not deter otherwise qualified applicants from applying. If you are an individual with a physical or mental disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities as part of our ongoing efforts to create an accessible workplace.
Qualcomm is an equal opportunity employer and supports workforce diversity.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
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