About the job
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. 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.
Responsibilities
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 & detection, 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. Develop and refine data-driven strategies for issue discovery and monitoring, enhanced by ML model outputs
Serve as the key link between AI/ML development and operational execution. Define and document new policies, guidelines, and Standard Operating Procedures (SOPs) that integrate AI tools and insights into daily vendor workflows.
Design and implement robust quality control processes for both human and AI-generated outputs. Perform meta-quality checks, validate the integrity of vendor work, and provide feedback to improve both human and model performance
Act as the subject matter expert for our Software Quality Operations, working closely with stakeholders, program leads, and vendor teams to ensure seamless adoption and maximum impact of AI/ML advancements in our quality processes. Be the trusted source for creating and updating technical policies, guidelines, and standard operating procedures for new scopes, platforms, and driving signals
Provide technical leadership and consultation to stakeholders to enhance our workflows and quality. You'll be at the forefront of identifying and escalating issues with our tools, providing technical requirements to engineering, and driving user testing to support the development and deployment of new tooling features
Scale workflow from 16/5 to 24/7 coordinating with external stakeholders, vendor team, and FTE team
Qualifications
Minimum
BS/BA degree and 4 years of relevant work experience in QC or AV Software Quality Operations
Increased competency in supporting all phases of the machine learning development life-cycle: data preparation, training, 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
A 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
Demonstrated strong execution with ability to drive outcomes
Ability to effectively and efficiently communicate with cross-functional stakeholders
Preferred
Experience working with offshore teams / multiple local operations hubs
Competency in LLM / transformer models, and / or ML for robotics domain experience
Basic SQL querying and PLX coding experience
Using subject matter expertise for results analysis and direct customer consultation in the development of new and improved solutions
Self-motivated with basic skills in task planning and time management
Experience assessing AV safety performance