Waymo
Engineering Operations Technical Specialist, Safety Dense Risk & Insights
Waymo, Detroit, Michigan, United States, 48228
Software Quality Operations Specialist, Safety Dense Risk & Insights
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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. It has provided over ten million rider-only trips and enabled the experience of autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
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. The SWQOps team plays a critical role in this expansion, making it possible to scale safely and efficiently. As part of SWQOps, the Tooling and Integrations team drives strategic initiatives that accelerate launch velocity for new products and automation.
This role reports to the SWQOps Safety Dense Risk & Insights Lead. The outputs of this team feed into key safety metrics, ML model training/automation validation, and a deeper understanding of the Driver’s safety performance and behaviors.
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 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 SOPs for new scopes, platforms, and driving signals.
Provide technical leadership and consultation to stakeholders to enhance our workflows and quality. Drive issue escalation, provide technical requirements to engineering, and lead user testing to support the development and deployment of new tooling features.
You Have
BS/BA degree and/or 4 years of relevant work experience in AV Software Quality Operations.
Strong 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-pace, 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 the ability to drive outcomes.
We Prefer
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 with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics.
The expected base salary range for this full-time position across US locations is
$120,000—$151,000 USD .
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.
Seniority level: Mid-Senior level.
Employment type: Full-time.
Job function: Quality Assurance; Industries: Technology, Information and Internet.
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Get AI-powered advice on this job and more exclusive features.
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. It has provided over ten million rider-only trips and enabled the experience of autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
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. The SWQOps team plays a critical role in this expansion, making it possible to scale safely and efficiently. As part of SWQOps, the Tooling and Integrations team drives strategic initiatives that accelerate launch velocity for new products and automation.
This role reports to the SWQOps Safety Dense Risk & Insights Lead. The outputs of this team feed into key safety metrics, ML model training/automation validation, and a deeper understanding of the Driver’s safety performance and behaviors.
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 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 SOPs for new scopes, platforms, and driving signals.
Provide technical leadership and consultation to stakeholders to enhance our workflows and quality. Drive issue escalation, provide technical requirements to engineering, and lead user testing to support the development and deployment of new tooling features.
You Have
BS/BA degree and/or 4 years of relevant work experience in AV Software Quality Operations.
Strong 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-pace, 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 the ability to drive outcomes.
We Prefer
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 with ML testing and validation, including dataset quality assurance, bias detection, edge-case scenario testing, and performance evaluation using statistical metrics.
The expected base salary range for this full-time position across US locations is
$120,000—$151,000 USD .
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.
Seniority level: Mid-Senior level.
Employment type: Full-time.
Job function: Quality Assurance; Industries: Technology, Information and Internet.
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