diffusion-models jobs in San Diego

Lead the scientific vision and execution of a generative AI platform for protein foundation models, starting with antibody and VHH design. You will build and manage a team of AI researchers and ML infrastructure engineers, define pretraining and post-training strategies across self-supervised learning, reinforcement learning, and transfer learning, and design confidence heads with out-of-distribution detection.…See more This is a founding role requiring deep expertise in structure-based generative modeling, multi-node GPU training, and the ability to shape cutting-edge computational approaches for therapeutic molecule discovery.

As an AI/ML advisor for biotherapeutics at Eli Lilly, you will lead training and fine-tuning experiments on proprietary infrastructure (LillyPod), curate and process biological data (sequences, structures, assays), and build evaluations that connect model outputs to experimental results. You will diagnose model failures, collaborate cross-functionally with protein scientists and wet-lab teams, and communicate findings to both computational and experimental audiences.…See more The role requires a Ph.D. in a quantitative field (or M.S. with 3+ years experience) and strong hands-on expertise in Python, PyTorch, and deep learning on GPUs, with preference for experience in geometric deep learning, protein language models, diffusion/flow-matching, and published ML applications to molecular data.

Principal System Lead responsible for translating AI-driven use cases into scalable, power-efficient implementations on Qualcomm's mobile SoCs. The role spans the full AI stack—generative AI, diffusion models, on-device inference, and camera-centric workloads—requiring deep knowledge of AI software frameworks and optimization across performance, latency, memory, and power constraints.…See more You will define system-level architectural enhancements for AI accelerators, CPUs, GPUs, and memory subsystems, working across hardware, software, and platform teams to align designs with OEM product roadmaps. The position demands 8+ years of semiconductor product development experience, 5+ years in technical leadership, and strong ability to solve complex AI system challenges through quantitative analysis and cross-functional collaboration.

Research Programmer III will develop machine learning and computational methods to understand behavior and neural activity in the Kennedy Lab at Scripps Research. The role involves building and training deep neural networks for supervised, unsupervised, and reinforcement learning problems, applying computer vision for high-throughput animal phenotyping, and contributing to scientific papers.…See more Candidates must have 4+ years of software development experience in Python with demonstrated expertise in deep learning, version control (git/GitHub), and software engineering principles. The position offers opportunities to lead independent research projects on datasets from collaborating institutions and is ideal for those building toward graduate studies in computational neuroscience or machine learning.

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.