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Waymo

Builds self-driving AI and runs a robotaxi service

Software Quality Operations Specialist

Manual & Functional QAConfirmed live in the last 24 hours
Full-timeLondon, UKIn-person

About the Job

Requirements

  • A bachelor's degree in a technical or analytical field, or at least five years of relevant work experience in autonomous vehicles, advanced driver-assistance systems, automotive systems engineering, robotics, or complex technical software operations.
  • An active, valid driver's license, extensive personal on-road driving experience, and thorough understanding of driving rules, roadway design, and regulations in Canadian and/or Australian metropolitan areas.
  • Competency in supporting all phases of the machine learning development lifecycle, from data preparation and training to validation, deployment, and continuous monitoring.
  • Experience with machine learning 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 use proprietary tools, and a strong understanding of driving rules and regulations.
  • Ability to work in a fast-paced, high-stress environment while maintaining good judgment and navigating technical ambiguity.
  • Communication and interpersonal skills to collaborate with individuals across a diverse work environment.

Responsibilities

  • Partner with Engineering to design, test, and deploy machine learning and generative AI models and tools to improve issue discovery and detection, triage efficiency, and quality assurance; provide Engineering with technical requirements for tooling that supports new-market workflows, such as localization of machine learning and generative AI models and new data pipelines.
  • Use AI-powered insights and traditional triage signals to 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 machine learning model outputs.
  • Define and document policies, guidelines, and standard operating procedures that integrate AI tools and insights into daily vendor workflows, serving as the link between AI and machine learning development and operational execution.
  • Design and implement quality-control processes for human- and AI-generated outputs; design and validate triage policies, standard operating procedures, and quality-control processes for Canadian and Australian driving rules, local infrastructure conventions, and regional driving conditions.
  • Serve as a subject matter expert for technical policies and guidelines in new markets and consult with local and international stakeholders to support adoption of those policies.
  • Provide technical leadership and consultation to stakeholders to improve workflows and quality; identify and escalate tool issues, provide technical requirements to Engineering, and drive user testing for new tooling features.
  • Triage driving events, discover issues, and conduct continuous field monitoring to provide early warnings and insights to Product and Data Science partners.
  • Conduct performance evaluation, issue deep-dives, and dataset curation to support Engineering, Systems Engineering, Simulation, and Data Science teams.
  • Incubate high-impact workflows and ensure readiness for automation and long-term operational excellence.

Desired Qualifications

  • Demonstrated ability to drive outcomes in new environments, from early-stage to mature operations.
  • Experience working with international and/or offshore vendor teams to drive global process standardization and quality.
  • Analytical skills and basic SQL querying.
  • Competency in large language model or transformer models, and/or machine learning experience in the robotics domain.
  • Subject matter expertise applied to results analysis and direct customer consultation in developing new and improved solutions.
  • Basic task-planning and time-management skills.
  • Experience with project or program management in a global, distributed environment.

About the Company

Waymo

Builds self-driving AI and runs a robotaxi service

Waymo builds self-driving technology and uses it to run a ride-hailing service in which passengers summon electric cars with no one behind the wheel. In 2020, it became the first company to open fully driverless rides to the public, starting in metro Phoenix. Its system, the Waymo Driver, pairs cameras, radar and laser sensors called lidar with onboard computers whose AI predicts what nearby people and vehicles will do and drives the car. Riders pay per trip through the Waymo app, or through Uber in some cities, while Waymo and fleet partners keep the cars charged and maintained. Waymo began as a Google project in 2009 and became a separate Alphabet company in 2016; it is based in Mountain View, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$32.1B
Headquarters
Mountain View, CA
Founded
2009

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