diffusion-models jobs in San Diego

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.

Qualcomm is seeking an AI Performance Engineer to optimize and deploy machine learning models for inference acceleration on cloud AI hardware. The role involves converting and optimizing language models, vision models, and diffusion models using PyTorch and ONNX, analyzing performance bottlenecks, and designing efficient kernels in Triton.…See more You will collaborate with compiler, firmware, and platform teams to map next-generation AI workloads onto hardware, working across the full product lifecycle from research to commercial deployment. The position requires deep expertise in transformer architectures, inference optimization techniques, computer architecture, ML accelerators, and distributed systems.

As a Datacenter AI Systems and Solutions Engineer at Qualcomm, you will research, develop, and optimize end-to-end AI/ML solutions that integrate Qualcomm's AI inference accelerators with system software and ecosystem components. You will lead the design and deployment of production-ready Generative AI and LLM applications, perform model benchmarking and performance analysis, and serve as a technical lead for customer engagements on AI model optimization and inference tuning.…See more The role requires deep expertise in AI systems architecture, MLOps practices, and large-scale distributed systems, with hands-on proficiency in Python, ML frameworks, containerization, and orchestration platforms. You will drive system-level requirements, hardware/software co-design, and influence product direction through performance analysis and optimization strategies.

Design and optimize video analysis and quality assessment algorithms for next-generation video codec hardware accelerators (FPGA/ASIC). Implement C-models and firmware for advanced video encoding, collaborating across algorithm, architecture, software, and hardware teams.…See more Apply machine learning techniques including deep learning frameworks and transformer architectures for ROI detection, content understanding, and feature extraction. Integrate algorithms into production VOD/live streaming workflows and validate impact through A/B testing and objective quality metrics (VMAF, PSNR, SSIM).

Design and optimize video analysis, quality assessment, and encoding algorithms for hardware-accelerated video codec solutions (FPGA/ASIC). Develop C-models and firmware for real-time video processing, implementing algorithms for ROI detection, content understanding, frame-level rate control, and objective quality metrics.…See more Collaborate with infrastructure and platform teams to integrate algorithms into production VOD and live-streaming workflows, validate performance through A/B testing, and optimize end-to-end video quality. The role requires strong programming skills in C/C++ or Python, knowledge of video quality standards (VMAF, PSNR, SSIM), and ideally experience with deep learning frameworks, video codecs, or embedded real-time systems.