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. 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. Waymo is experiencing unprecedented growth, rapidly expanding into new cities and launching new vehicle platforms. SWQOps, particularly our Technical Specialists, are critical to this expansion, enabling us to scale safely and efficiently. Why this team is Essential to Waymo's Success: In this role 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. - 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. 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. - Must have the ability to work a flexible schedule, including some weekends and holidays, as needed. We prefer: - Demonstrated strong execution with ability to drive outcomes. - Experience working with offshore teams / multiple local operations hubs. - Basic SQL querying. - Competency in LLM / transformer models, and / or ML for robotics domain experience. - A greater focus on using your 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. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $130,000—$160,000 USD

• Own AI-led QA system expansion into complex domains • Design and operationalize quality signals at scale • Drive signal accuracy and trust • Translate ambiguous quality problems into structured systems • Influence the QA tech and model roadmap • Establish durable process frameworks • Lead cross-functional execution across Product, Engineering, Ops, and Policy

• Support ongoing quality assurance across data-intensive web applications and microservice-based platforms • Work with both UI and API testing frameworks across multiple stacks • Maintain existing test suites and contribute to automation initiatives

Job Title: Quality Assurance Engineer Position Type: Full-Time, Remote Working Hours: U.S. client business hours (with flexibility for release cycles, sprint deadlines, and testing windows) About the Role: Our client is seeking a QA Tester / Quality Assurance Engineer to design and execute test plans, identify defects, and ensure software applications meet functional and performance requirements before release. This role combines manual and automated testing, documentation, and collaboration with developers and product teams to safeguard product quality. Responsibilities: Test Planning & Design: - Develop comprehensive test plans, test cases, and acceptance criteria. - Collaborate with product managers and developers to understand requirements and user stories. - Define test coverage for features, integrations, and regression. Manual Testing: - Execute functional, regression, UI/UX, cross-browser, and cross-device testing. - Log bugs in Jira, Azure DevOps, or similar tools with clear reproduction steps. - Verify bug fixes and retest impacted areas. Automated Testing: - Build and maintain automated test scripts with tools like Selenium, Cypress, or Playwright. - Integrate automated tests into CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI). - Monitor and troubleshoot test automation failures. Performance & Security Testing: - Conduct load/stress testing with JMeter or Locust. - Support security vulnerability scans and penetration test remediation. Documentation & Reporting: - Maintain updated documentation of test plans, cases, and results. - Provide detailed reports on test execution, defect trends, and quality metrics. - Track quality KPIs (defect density, test coverage, pass/fail ratios). Collaboration: - Work closely with developers to reproduce, isolate, and resolve defects. - Participate in sprint ceremonies and advocate for quality in Agile workflows. - Provide feedback on product design for usability and testability. What Makes You a Perfect Fit: - Detail-oriented and relentless in uncovering issues. - Strong communicator who documents clearly for both technical and non-technical stakeholders. - Comfortable balancing speed of delivery with thorough quality coverage. - Proactive problem solver who anticipates edge cases and risks. Required Experience & Skills (Minimum): - 2+ years QA or software testing experience. - Proficiency with test management and bug-tracking tools (Jira, TestRail, Zephyr). - Familiarity with test automation frameworks (Selenium, Cypress, Playwright). - Strong understanding of SDLC and Agile methodologies. Ideal Experience & Skills: - Industry experience in SaaS, finance, healthcare, or enterprise software. - Familiarity with API testing tools (Postman, RestAssured). - Exposure to security testing or compliance-heavy environments. - Experience integrating QA into CI/CD pipelines. What Does a Typical Day Look Like? A QA Tester’s day revolves around validating functionality and preventing defects from reaching production. You will: - Start by reviewing requirements and user stories to design or refine test cases. - Execute manual and automated tests on new features and bug fixes. - Log defects with detailed notes for developers, collaborating on reproduction. - Participate in daily standups, providing quality updates on ongoing sprints. - Review regression test results after each build or deployment. - Update test documentation and report quality metrics to leadership. In essence: you are the last line of defense before release, ensuring products meet quality standards and deliver a reliable user experience. Key Metrics for Success (KPIs): - Defect detection rate before production release. - Regression test coverage percentage. - Time-to-resolution of logged bugs. - % of releases deployed without critical/severe defects. - Positive stakeholder confidence in product quality. Interview Process: - Initial Phone Screen - Video Interview with Pavago Recruiter - Practical Task (e.g., design a test plan or execute a sample bug test case) - Client Interview with QA/Engineering Leadership - Offer & Background Verification