edge-inference jobs in San Diego

As an Autonomy Engineer focused on VLA (Vision-Language-Action) pre-training, you will develop and train deep learning policies for humanoid robots, owning the full pipeline from data collection and curation to model deployment. You'll pre-train base models on diverse multi-embodiment trajectory corpora, fine-tune policies for specific tasks, work with MLOps teams to scale distributed training, and build continuous pipelines that ingest synthetic data and teleop logs.…See more This is primarily a deep learning role requiring 3+ years of experience shipping neural network models, hands-on expertise with LLMs, VLMs, or generative models, and strong proficiency in Python and PyTorch or JAX.

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.