neural-network-optimization jobs in San Diego

Principal Software Engineer role on Qualcomm's Cloud AI team focused on LLM serving and inference acceleration. The engineer will design, optimize, and deploy high-performance software across the product lifecycle, from R&D through commercial deployment, with expertise in serving frameworks (vLLM), PyTorch, neural network optimization, and multi-core/SoC architecture performance modeling.…See more Strong C++/Python development skills, deep LLM/multi-modal model understanding, and experience with machine learning accelerators are required; experience with compiler technology, performance analysis, and commercial software delivery at scale is essential.

Design, architect, and deploy on-device AI prototype software for edge computing applications at Qualcomm's AI Research division. You will work with modern deep learning frameworks (PyTorch), optimize neural network models for embedded deployment, and integrate cutting-edge AI technologies into mobile, IoT, and autonomous systems.…See more The role requires strong Python and C/C++ skills, deep learning expertise, embedded software development experience, and solid software engineering fundamentals.

Senior ML engineer role focused on architecting, designing, and deploying on-device AI prototype software at the edge. Requires strong Python and C/C++ skills, deep learning expertise (PyTorch), and embedded software development experience.…See more The role involves model fine-tuning, quantization, hardware acceleration, and inference optimization for deployment on smartphones, autonomous vehicles, IoT, and robotics platforms. Must have 3+ years relevant experience and a strong theoretical ML background combined with modern software engineering practices.

Senior Machine Learning Engineer responsible for architecting, designing, developing, and deploying on-device AI prototype software for edge computing applications. The role requires expert-level proficiency in C++ and Python, deep knowledge of ML frameworks like PyTorch, and hands-on experience with low-level system debugging, performance tuning, and native inference driver development.…See more You will work in a multi-disciplinary research team advancing generative AI technology for the edge, including model fine-tuning, hardware acceleration, model quantization, and edge inference. A strong theoretical background in deep learning combined with embedded software development experience and modern software engineering best practices is essential.

Join Qualcomm AI Research as a Machine Learning Engineer to architect, design, develop, and deploy on-device AI prototype software for edge devices. You will work with a multi-disciplinary team using cutting-edge AI frameworks, focusing on model fine-tuning, quantization, and edge inference.…See more Strong Python, deep learning frameworks (PyTorch), object-oriented design, and software engineering best practices are required. Preferred qualifications include generative AI knowledge, neural network optimization, NPU/ML accelerator experience, Android programming, C/C++, and embedded software skills.