Qualcomm

General Summary: We’re seeking a multidisciplinary engineer with strong expertise in computer vision algorithms and SoC/hardware architecture. This role is ideal for someone who thrives at the intersection of cutting‑edge AI models and efficient hardware implementation. You’ll design segmentation algorithms, optimize modern deep learning architectures, and help shape the hardware that runs them. Responsibilities Develop and optimize computer vision algorithms, with emphasis on segmentation and real‑time performance.Implement and tune state‑of‑the‑art efficient AI architectures, including Transformers, Mamba‑style sequence models, and attention‑optimization techniques such as FlashAttention.Collaborate with hardware and SoC teams to co‑design accelerators and pipelines for CV and ML workloads.Profile and optimize model performance across memory, compute, and bandwidth constraints.Contribute to system‑level architecture decisions for next‑generation CV/AI products.Work closely with firmware and software teams to deploy models on embedded or edge platforms. Qualifications Strong background in computer vision, especially segmentation (classical and deep learning–based).Solid understanding of SoC architecture, including compute accelerators, memory hierarchy, and hardware/software interfaces.Hands‑on experience with modern deep learning architectures:Transformers and efficient transformer variantsFlashAttention or similar attention‑optimization techniquesMamba or other state‑space modelsSOTA efficient models (e.g., MobileNet‑style, ConvNeXt, lightweight segmentation networks) Proficiency in Python and C/C++, plus experience with ML/CV frameworks (PyTorch, TensorFlow, ONNX, OpenCV).Familiarity with hardware modeling, FPGA prototyping, or RTL design is a plus.Strong ability to work across algorithm, software, and hardware boundaries. Preferred Experience Algorithm–hardware co‑design for edge AIQuantization, pruning, distillation, or other model‑efficiency techniquesReal‑time CV systems or embedded AI deploymentPerformance profiling tools and hardware simulatorsMinimum 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.ORMaster'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.ORPhD in Computer Science, Engineering, Information Systems, or related field.

Qualcomm stands as a beacon of innovation, pioneering the forefront of on-device AI and unlocking the transformative potential of 5G. Our breakthroughs herald an era of unparalleled connectivity, sparking possibilities that will reshape industries, generate employment, and enrich lives. At the heart of this revolutionary era, Qualcomm's commitment to on-device AI leadership stands unmatched. Shaping 5G's potential into world-altering technologies demands inventive minds, diverse skills, and cultural backgrounds—a defining epoch known as the Age of Invention.Are you poised to immerse yourself in the forefront of technological evolution, comparable in significance to the advent of the Internet? Machine learning is poised to revolutionize EVERYTHING. In Taiwan, our AI Software Engineering team, collaborating extensively with global AI RD teams, is at the helm of Qualcomm's pioneering advancements.Join us in leveraging your skills to expand Qualcomm's trailblazing AI portfolio (Qualcomm AI Stack), with a distinct emphasis on a software platform tailored for AI applications in Mobile, Automotive, IoT, and HPC devices, establishing our leadership in the AI PC domain.We integrate cutting-edge hardware with high-performance software, empowering rapid execution of deep neural networks on our unparalleled range of Snapdragon processors, setting the benchmark for minimal power consumption. Your role here is pivotal, enabling advanced machine learning scenarios atop Qualcomm's hardware and software infrastructure. You'll contribute to system software, tool development, maintenance, and evolution for various ML computing SDKs tailored for Qualcomm processors, both on Windows OS and Android OS.Amplifying the SDK's capabilities, collaborate with neural network frameworks like PyTorch and TensorFlow. Extend our neural net engine to support the latest DNNs emerging from the research community and optimize for the next-gen hardware acceleration cores.Validate engine performance and accuracy through meticulous analysis and comprehensive test coverage. Thrive in software development, wielding exceptional analytical, development, and debugging skills.Partner with industry leaders to usher in the next generation of machine learning technology, solidifying Qualcomm's pioneering stance in the AI PC domain.