time-series-forecasting jobs in San Diego

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

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.

Own end-to-end demand forecasting and capacity planning for AI systems, compute, storage, GPU, and emulation across a global engineering organization spanning tens of thousands of servers and hundreds of petabytes of storage. Translate silicon product roadmaps and tapeout schedules into multi-year demand plans, size and justify capital purchases into the hundreds of millions of dollars, and present capacity positions to engineering and finance leadership.…See more Build and maintain forecasting models, decision rules, and utilization analytics; apply AI and automation to move beyond manual spreadsheet work. Lead and mentor a team of analysts, raising their craft and setting analytical direction.