Nutanix
Company
Qualcomm Technologies, Inc. Job Area
Engineering Group, Engineering Group > Machine Learning Engineering General Summary
The Qualcomm GPU Software team is looking for talented software engineers interested in developing software for the latest Machine Learning models on the next generation of devices. The GPU Software team is responsible for delivering device drivers, extensions for Machine Learning and tools for Snapdragon chipsets, providing best in class performance, power, and features. This role will involve working on Graphics software stack and Machine Learning SDKs and frameworks on Android, Linux and Windows. As a GPU Software Machine Learning Engineer, you are responsible for working with a team that is developing & optimizing Adreno GPU drivers for standard APIs such as OpenCL, OpenGL ES, Vulkan, and DirectX. You will be exposed to technology areas such as Image Processing and Machine Learning. This position requires close collaboration with hardware designers to understand, improve, and document hardware/software interfaces. Responsibilities will include the acceleration of Machine Learning operations for inference and training on the GPU, implementation of the latest Machine Learning models including LLMs and LVMs, writing samples and documentation, implementing interfaces to Machine Learning frameworks, development of unit tests and working with our partners, external developers, and OEMs. Skills
Strong C/C++ programming skills Strong knowledge of Machine Learning Theory Familiarity with a Deep Learning Framework such as PyTorch Familiarity with a GPGPU API such as CUDA or OpenCL Understanding of data structures and algorithms, including object-oriented programming Excellent interpersonal and analytical skills with the ability to work independently Optional, preferred skills
Device driver development, including GPU or CPU Programming experience with Graphics APIs such as OpenGL ES/Vulkan/DX11/DX12 Knowledge of GPGPU application development including Mathematical Operations and Image Processing Exposure to Embedded systems and Real-time operating systems Experience working with ARM architecture Familiarity with Git or other SCM tools 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. Preferred Qualifications
Master\'s Degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field. 3+ years\' experience with software development skills (e.g. data structure and algorithm design, object oriented or other software design paradigm knowledge, software debugging and testing, etc.) 3+ years\' experience with C++ programming Optimizing algorithms for GPU hardware using OpenCL or CUDA Experience with different NN architectures such as CNNs, LLMs, LVMs, etc. Background in mathematical operations (e.g. linear algebra, fast math libraries, etc.) Principal Duties and Responsibilities
Writes code for well-defined features, drivers, and APIs using different languages (e.g., C, C++, Python). Assists in identifying deficiencies in designs and works with team members to develop solutions to improve designs. Collaborates with team members to understand new features and functionality that align with needs and goals for implementation and customization. Writes detailed design documentation and feature descriptions for projects. Equal Opportunity and Accommodation
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 email 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 is also committed 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 regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification. Pay range and Other Compensation & Benefits: $140,800.00 - $211,200.00 The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Salary is one component of total compensation at Qualcomm, which also includes a discretionary bonus and potential RSU grants. Details about US benefits can be discussed with your recruiter. If you would like more information about this role, please contact Qualcomm Careers.
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Qualcomm Technologies, Inc. Job Area
Engineering Group, Engineering Group > Machine Learning Engineering General Summary
The Qualcomm GPU Software team is looking for talented software engineers interested in developing software for the latest Machine Learning models on the next generation of devices. The GPU Software team is responsible for delivering device drivers, extensions for Machine Learning and tools for Snapdragon chipsets, providing best in class performance, power, and features. This role will involve working on Graphics software stack and Machine Learning SDKs and frameworks on Android, Linux and Windows. As a GPU Software Machine Learning Engineer, you are responsible for working with a team that is developing & optimizing Adreno GPU drivers for standard APIs such as OpenCL, OpenGL ES, Vulkan, and DirectX. You will be exposed to technology areas such as Image Processing and Machine Learning. This position requires close collaboration with hardware designers to understand, improve, and document hardware/software interfaces. Responsibilities will include the acceleration of Machine Learning operations for inference and training on the GPU, implementation of the latest Machine Learning models including LLMs and LVMs, writing samples and documentation, implementing interfaces to Machine Learning frameworks, development of unit tests and working with our partners, external developers, and OEMs. Skills
Strong C/C++ programming skills Strong knowledge of Machine Learning Theory Familiarity with a Deep Learning Framework such as PyTorch Familiarity with a GPGPU API such as CUDA or OpenCL Understanding of data structures and algorithms, including object-oriented programming Excellent interpersonal and analytical skills with the ability to work independently Optional, preferred skills
Device driver development, including GPU or CPU Programming experience with Graphics APIs such as OpenGL ES/Vulkan/DX11/DX12 Knowledge of GPGPU application development including Mathematical Operations and Image Processing Exposure to Embedded systems and Real-time operating systems Experience working with ARM architecture Familiarity with Git or other SCM tools 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. Preferred Qualifications
Master\'s Degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field. 3+ years\' experience with software development skills (e.g. data structure and algorithm design, object oriented or other software design paradigm knowledge, software debugging and testing, etc.) 3+ years\' experience with C++ programming Optimizing algorithms for GPU hardware using OpenCL or CUDA Experience with different NN architectures such as CNNs, LLMs, LVMs, etc. Background in mathematical operations (e.g. linear algebra, fast math libraries, etc.) Principal Duties and Responsibilities
Writes code for well-defined features, drivers, and APIs using different languages (e.g., C, C++, Python). Assists in identifying deficiencies in designs and works with team members to develop solutions to improve designs. Collaborates with team members to understand new features and functionality that align with needs and goals for implementation and customization. Writes detailed design documentation and feature descriptions for projects. Equal Opportunity and Accommodation
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 email 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 is also committed 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 regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification. Pay range and Other Compensation & Benefits: $140,800.00 - $211,200.00 The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Salary is one component of total compensation at Qualcomm, which also includes a discretionary bonus and potential RSU grants. Details about US benefits can be discussed with your recruiter. If you would like more information about this role, please contact Qualcomm Careers.
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