model-drift-detection jobs in San Diego

Staff Quality Analyst role responsible for building dashboards and analytics that surface defect signals and drive leadership decision-making at scale. The role combines hands-on data analysis (SQL, Python, statistics) with AI-native workflows to accelerate defect detection and root cause analysis, plus structured change management to land measurement and process changes across large stakeholder groups.…See more Required skills include strong SQL/Python proficiency, applied statistics, experience with defect frameworks (DPMO), contact center operations familiarity, and demonstrated ability to communicate data findings credibly to executives and manage organizational change.

Design and architect next-generation ML inference infrastructure for globally distributed, multi-tenant model serving with high availability, scalability, and cost efficiency. Lead the development of low-latency, high-throughput inference systems supporting computer vision and multimodal models (CNNs, segmentation, object detection) using Scala, Java, and Go.…See more Build large-scale distributed systems with reactive frameworks, integrate enterprise feature stores, and extend CI/CD pipelines (GitHub Prow, Pulumi) with automation and policy enforcement. Design advanced observability frameworks, optimize ML algorithms for performance, mentor engineers, and ensure MLOps and compliance standards (GDPR, SOC2) across the platform.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams.…See more The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.