**Company:** Qualcomm Semiconductor Limited **Job Area:** Engineering Group, Engineering Group > Systems Engineering **General Summary:** Qualcomm Computer Vision Systems group provides Vision IP solutions for all of Qualcomm’s Snapdragon processors including mobile, automotive and VR/AR. The team’s scope includes computer vision algorithms, architecture design for CV accelerators and hardware modeling with power and performance optimization. We seek Systems Engineers with demonstrable knowledge and hands-on experience with system modeling for design verification & validation, pre-silicon emulation support for FW & SW. The selected candidate, along with his/her colleagues and other team members, will have responsibilities in one or more of the following areas: + Modeling of Computer Vision algorithms & architecture, including data flow, task partition, interface and systems interoperation + Modeling in C/C++ under both Windows & Linux dev. environments + Optimizing models on CPU for memory and run time performance + Work on DSP or GPU optimization of computer vision algorithms + Deploy simulation models acceleration on CPU / GPU through multi-threading, parallelization, or cloud deployment + Scripting in Python for Unit and System testing. + Performing version control (Perforce) & code-tip maintenance using test automation + Managing large codebase integration & testbench automation + Collaborate with systems, software, hardware teams at various stages of chipset life in design/validation/commercialization. + Working within a fast-paced & collaborative environment with geographically & functionally distributed teams **Qualifications** + Required: Bachelors in, Computer Science and/or Electrical Engineering + Preferred: Masters or Doctorate, Computer Science and/or Electrical Engineering **Minimum Skills** + Proficiency in C/C++/Python coding and debugging + Working Knowledge of Embedded systems and architectures **Preferred Skills** + Working experience with embedded accelerators, hardware component modeling, SoC Modeling + Experience with computer vision and machine learning techniques + DSP/Neon/GPU optimization and multi-thread programming + Working experience in one or more of GPU, OpenMP/OpenCL, SIMD + Additional working experience on CUDA + Experience with any of Jenkins, Linux (csh/bash), Windows, Python and its ecosystem, **Minimum Qualifications:** • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience. **Applicants** : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that 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 (https://qualcomm.service-now.com/hrpublic?id=hr\_public\_article\_view&sysparm\_article=KB0039028) . 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. 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Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) . 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