vision-language-models jobs in San Diego

Design and develop embedded and cloud edge software applications focused on AI/GenAI, multimedia, and computer vision SDKs and frameworks for IoT products including drones, cameras, and AI boxes. Collaborate with systems, hardware, and architecture teams to build high-performance, real-time embedded software solutions.…See more Lead GenAI LLM/VLM inference workflows, multi-stream AI pipelines, and multimedia frameworks across Android, Linux, and embedded systems. Requires 2+ years of software engineering experience with C/C++, Python, or Java, plus preferred expertise in PyTorch, TensorFlow, ONNX Runtime, LangChain, LlamaIndex, Android architecture, Linux system programming, and graphics/GPU pipelines.

As a Senior Software Engineer focused on AI Tools, you will reauthor and optimize generative AI models (LLMs like Llama, Phi, Qwen, and multimodal models) for efficient execution on Qualcomm's on-device hardware. You'll translate hardware constraints into model-level transformations that preserve accuracy while enabling edge deployment, integrate inference acceleration techniques, and collaborate with compiler and quantization teams to move research prototypes into production.…See more The role requires deep implementation-level knowledge of generative AI architectures, strong Python proficiency in large typed codebases, and hands-on experience optimizing inference for resource-constrained environments.

Conduct cutting-edge research in efficient generative AI, including LLMs, multi-modal foundation models, LLM reasoning, reinforcement learning, and agentic AI. Lead high-impact research initiatives and develop production-ready solutions with real-world commercial impact, with a focus on on-device deployment challenges.…See more Implement and evaluate solutions in both simulation and on-device environments, and publish findings in top-tier AI/ML conferences. Requires a Master's degree and 2+ years of experience (or PhD), with proven research excellence, deep expertise in generative AI and reinforcement learning, and hands-on experience with model development pipelines including training, fine-tuning, evaluation, and optimization.