About the job
The Software Quality Operations (SWQOps) team is at the heart of ensuring the safety, reliability, and quality of the Waymo Driver. Our mission is to build an adaptable and scalable operation, increasingly powered by AI, to deliver the crucial insights necessary to confidently deploy and grow Waymo's autonomous vehicle service. The Safety Operations team within SWQ Ops owns the scale delivery of datasets and methodologies used to evaluate the Safety and performance of the driver as Waymo continues to scale.
Responsibilities
Drive the strategy and technical implementation of decomposing complex safety triage workflows and develop advanced operational and ML techniques to enable automation.
Serve as the subject matter expert for human-in-the-loop ML systems in the safety problem space and define requirements for generating high-quality human feedback to optimize ML models performance.
Partner with Engineering to design, test, and deploy cutting-edge Machine Learning (ML) and Generative AI (Gen-AI) models and tools to drive improvements in issue discovery, triage efficiency, and quality assurance.
Leverage AI-powered insights and traditional triage signals to proactively identify emerging on-road issue trends, new risk scenarios, and edge cases.
Serve as the key link between AI/ML development and operational execution by authoring foundational technical policies, standards, strategic roadmaps, and process blueprints.
Advise senior stakeholders on the long-term technical strategy and operational capabilities of the organization.
Qualifications
Minimum
BS/BA degree or 7+ years of relevant work experience in AV Software Quality Operations / ML Operations.
Proven ability to manage complex, technical projects and experience working across technical partners (Product, Engineering, Data Science, Systems Engineering) to drive outcomes.
Increased competency in supporting all phases of the machine learning development lifecycle, from data preparation and training to validation, deployment, and continuous monitoring.
Experience with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics.
Ability to quickly learn and implement new concepts and utilize proprietary tools.
Strong understanding of driving rules and regulations.
Proven ability to work in a fast-paced, high-stress environment while maintaining good judgment.
Excellent communication and interpersonal skills to effectively collaborate with a wide range of individuals in a diverse and dynamic work environment.
Preferred
Undergraduate in technical degree preferred.
Experience within A / V space.
Competency in LLM / transformer models, and / or ML for robotics domain experience.
Competency in SQL querying / data analysis.
Experience working with offshore teams / multiple local operations hubs.