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Opportunity
Operations

Software Quality Operations Specialist

Waymo · Triage (SQW)

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Pay
$130,000–$160,000/yr
Where
Remote
Posted
Jun 8

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver.

What you'd do

  • Support the development of a single, automated, end-to-end machine learning flywheel for the entire Waymo Driver: 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 triage of driving events, issue discovery, and field monitoring, SWQOps provides early warnings and critical insights.
  • This "early intervention in RO issue detection" ensures operational resilience and safety which is critical as Waymo enters multiple new cities and ramps up platforms like W12.
  • Enabling Market Expansion which will allow 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.
  • 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
  • Be a main link between AI/ML development and operational execution. Define and document new policies, and Standard Operating Procedures (SOPs) that integrate AI tools and insights into daily vendor workflows.
  • Design and implement 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.
  • Be the subject matter expert for our Software Quality Operations, working with partners, program lead, 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 guidelines, and standard operating procedures for new scopes, platforms, and driving signals
  • Provide technical leadership and consultation to partners to enhance our workflows and quality.
  • You'll identify and escalate issues with our tools, providing technical requirements to engineering, and driving user testing to support the development and deployment of new tooling features.

What they want

  • 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 monitoring.
  • Experience with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics.
  • Implement new concepts and use proprietary tools.
  • Experience with driving rules and regulations.
  • Problem solve and make data-informed decisions.
  • Collaborate with many individuals in a diverse work environment
  • Demonstrated execution with an ability to improve outcomes
  • Experience working with offshore teams / multiple local operations hubs
  • Basic SQL querying