foundation-models jobs in San Diego

Lead end-to-end AI platform architecture and infrastructure at enterprise scale, designing and implementing generative AI capabilities including LLMs, RAG systems, and agentic AI with a focus on model serving, inference optimization, and production deployment. Establish MLOps/LLMOps best practices, build automated CI/CD pipelines tailored for AI/ML applications, and architect vector database integration and cloud AI/ML services.…See more Mentor engineering teams, drive cross-functional collaboration between software, product, and data teams, and continuously evaluate and optimize AI platform performance, scalability, and reliability.

Lead enterprise AI platform strategy and execution at a biotech company, driving end-to-end program delivery across engineering, data, cybersecurity, and product teams. Own platform health, KPIs, and telemetry; establish governance, safety guardrails, and regulatory compliance for AI-enabled solutions in a regulated environment.…See more Define multi-year AI roadmaps, coordinate cross-functional dependencies, and orchestrate Agile delivery while partnering with legal, compliance, and tech enablement to ensure scalability, security, and enterprise adoption.

Build applied AI systems for Crucible, Firestorm's manufacturing operations software. You'll productionize ML and optimization models, integrate foundation models and LLMs into workflows, and design end-to-end AI capabilities—from model selection and evaluation through reliable production deployment across cloud, air-gapped, and edge environments.…See more This is a hands-on engineering role requiring 5+ years shipping production ML/AI systems, strong Python and software engineering fundamentals, and deep experience with LLMs, transformer models, and production ML monitoring.

Senior Manager leading R&D strategy for digital health and AI/ML solutions in neuropsychiatry at a major pharmaceutical company. The role spans developing and validating digital endpoints, patient stratification approaches, and clinical trial optimization using advanced statistical modeling, multimodal data integration (digital phenotyping, speech/language analytics, imaging, biomarkers, omics), and longitudinal analysis.…See more Requires 6+ years in pharma/biotech analytics with demonstrated expertise in clinical development, digital health technologies, biostatistics, and machine learning; PhD or MD in a quantitative or clinical field preferred. Reports to senior leadership, partnering cross-functionally with clinical operations, regulatory affairs, and external collaborators to advance digital health standards and support regulatory qualification of novel endpoints.

Lead end-to-end AI platform architecture and design for generative AI solutions, including LLMs, RAG systems, and agentic AI. Build MLOps/LLMOps pipelines with automated CI/CD, model serving infrastructure, and vector database integration on enterprise cloud platforms.…See more Establish best practices, mentor engineering teams, and drive seamless AI application integration into production systems while optimizing for scalability, security, and performance.

Design and build large-scale multimodal foundation models that integrate high-dimensional biomedical imaging with molecular and language data. You will implement cross-domain data fusion strategies, develop high-performance ML pipelines for petabyte-scale datasets, and collaborate with scientists and engineers to translate biological complexity into scalable, production-ready code.…See more The role requires deep expertise in Computer Vision architectures, distributed training frameworks, and expert Python proficiency. You will contribute through high-impact publications or open-source work and demonstrated ability to handle the noise and sparsity inherent in biological data.

Qualcomm seeks a Machine Learning R&D leader to design and deliver Agentic AI systems for hardware design automation. The role combines hands-on technical execution with team leadership, requiring deep expertise in generative AI, large language models, and ML/AI product development.…See more Responsibilities include architecting end-to-end ML solutions, coaching an interdisciplinary team of researchers and engineers, and bridging research prototypes into production design tools. The ideal candidate brings PhD-level credentials, 2+ years of industry ML/GenAI experience, and proven expertise in agentic AI frameworks, foundation models, and complex ML software pipelines.