Ops Specialist, Regulatory Reporting

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.

Why This Team is Essential to Waymo's Success: 

Waymo is undergoing unprecedented growth, rapidly expanding into new cities (targeting ~20 new cities by EOY 2026) and launching new vehicle platforms. SWQOps, especially our Technical Specialists, plays a critical role in this expansion, making it possible to scale safely and efficiently. We are on the front lines of: 

• Supporting the development of a single, automated, end-to-end machine learning flywheel for the entire Waymo Driver. A successful flywheel will be the core engine for scaling our technology, enabling faster ODD expansion, quicker remediation of driving issues, and a significant reduction in the engineering effort required to maintain and improve the driver.
• De-risking New Deployments: Through meticulous triage of driving events, issue discovery, and continuous field monitoring, SWQOps provides early warnings and critical insights. This "early intervention in RO issue detection" ensures operational resilience and safety, particularly in new and complex environments, which is critical as Waymo enters multiple new cities and ramps up platforms like W12. 
• Enabling Market Expansion: Our team is deeply integrated into every stage of Waymo's market entry framework, from initial city evaluation (OK2Plan) to scaling operations (OK2Scale). We provide the necessary data analysis, policy development, and quality assurance to unblock critical milestones, preventing slowdowns in market expansion velocity. 
• Driving Engineering Velocity: By handling the vital work of performance evaluation, issue deep-dives, and data set curation, SWQOps collaborates heavily and allows Waymo's Engineering, SysEng, Simulation, and Data Science teams to focus on their core tasks of developing and improving the Waymo Driver.

You will:

• Partner with Engineering to design, test, and deploy cutting-edge Machine Learning (ML) and Generative AI (Gen-AI) models and tools to drive step-change 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.

You have:

• BS/BA degree or 4 years of relevant work experience in AV Software Quality Operations
• 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.
• 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

We prefer:

• Experience working with offshore teams / multiple local operations hubs
• Competency in LLM / transformer models, and / or ML for robotics domain 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 with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics.
• Competency in supporting all phases of the machine learning development lifecycle, from data preparation and training to validation, deployment, and continuous monitoring.