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Staff Engineer, Machine Learning Engineering (On-device SW)

Staff Engineer, Machine Learning Engineering (On-device SW)

NutanixSan Diego, CA, United States
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Company :

Qualcomm Technologies, Inc.

Job Area :

Engineering Group, Engineering Group >

Machine Learning Engineering

General Summary :

Qualcomm AI Research is looking for talented AI software engineers to enable AI technologies on edge devices. This is your opportunity to join a high-caliber team of engineers, building best-in-class GenAI solutions with model optimization tools to deploy state-of-the-art models to edge devices with optimal power, memory, and computation use.

In this role, you will be part of a multi-disciplinary team that has continually enabled first-of-its-kind and competitive generative AI models on Qualcomm AI accelerator engines, such as the world’s first on device text-to-image generation with stable diffusion, and text-to-text with 7B large language model on device.

You will collaborate in a cross-functional environment spanning hardware, software and systems and see your design in action on industry-leading chips embedded in the next generation of intelligent devices, such as smartphones, autonomous vehicles, robotics, and IOT devices.

Minimum Qualifications :

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • OR Master’s degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • OR PhD in Computer Science, Engineering, Information Systems, or related field.

Responsibilities :

  • Development of end-to-end embedded AI software to run quantized neural network models on Qualcomm leading edge hardware with optimal resources.
  • Design and enhance the implementation of ML / AI software stack, kernels, and runtime software to improve performance and power efficiency.
  • Collaborating with our AI Processor Hardware team to implement high-quality solutions for new ML operators / layers that optimally utilize new capabilities in next-gen AI processors.
  • Development of debugging / profiling tools and user-friendly SDKs for customers to foster rapid deployment of their new use cases.
  • Preferred Skills and Experience :

  • 3+ years of professional work experience in a relevant field.
  • Excellent programming capabilities with C / C++ and Python.
  • Knowledge of deep learning and ML frameworks (i.e. PyTorch).
  • Strong software design, development, and debugging skills.
  • Knowledge of Android programming is a plus.
  • Optimization of algebraic operations in algorithms for HW cores is a plus.
  • Knowledge in neural network model quantization is a big plus.
  • Experience with Qualcomm QNN SDK is a big plus.
  • Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application / hiring process, Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm’s toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm also commits to making our workplace accessible for individuals with disabilities.

    EEO Employer : Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

    Pay range and Other Compensation & Benefits : $158,400.00 - $237,600.00. The pay scale reflects the broad range for this job code / location. Salary is one component of total compensation, which may include discretionary bonus and RSU grants. Details about benefits are available from the recruiter.

    If you would like more information about this role, please contact Qualcomm Careers.

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