资深软件质量安全运营专员
Staff Software Quality Safety Operations Specialist
Waymo 是一家自动驾驶技术公司,使命是成为全球最受信赖的驾驶员。自 2009 年作为 Google 自动驾驶汽车项目启动以来,Waymo 一直专注于打造 Waymo Driver——全球经验最丰富的驾驶员™,以提升出行可及性,同时减少因交通事故而失去的数千条生命。Waymo Driver 驱动着 Waymo 的完全自动驾驶叫车服务,也可应用于多种车辆平台和产品使用场景。Waymo Driver 已经提供了超过一千万次仅乘客行程,这得益于其在公共道路上自主驾驶超过一亿英里,以及在美国 15 个以上州进行的数十亿英里的模拟。
软件质量运营(SWQOps)团队是确保 Waymo Driver 安全性、可靠性和质量的核心。我们的使命是构建一个灵活且可扩展的运营体系,越来越多地由人工智能驱动,以提供关键洞察,从而有信心地部署和扩展 Waymo 的自动驾驶汽车服务。
为什么这个团队对 Waymo 的成功至关重要:
Waymo 正经历前所未有的增长,正在迅速扩展到新城市(目标是在 2026 年底前进入约 20 个城市),并推出新的车辆平台。SWQ Ops 在这一扩展中发挥着关键作用,使我们能够安全高效地扩展。SWQ Ops 内部的安全运营团队负责安全和性能评估所使用的数据集和方法论的规模交付,随着 Waymo 的持续扩展,我们处于以下前线:
- 降低新部署风险:通过细致的驾驶和模拟事件分类、问题发现和持续现场监控,SWQOps 提供早期预警和关键洞察。这种“在 RO 问题检测中的早期干预”确保了运营弹性和安全性,特别是在新且复杂的环境中,这对于 Waymo 进入多个新城市并加快 Ojai 等平台的推进至关重要。
- 提升工程速度:通过处理性能评估、问题深入分析和数据集整理等关键工作,SWQOps 与 Waymo 的工程、系统工程、模拟和数据科学团队紧密协作,使他们能够专注于开发和改进 Waymo Driver 的核心任务。
- 支持市场扩展:我们团队深度参与 Waymo 市场进入框架的每个阶段,从初始城市评估(OK2Plan)到运营扩展(OK2Scale)。我们提供必要的数据分析
查看英文原文
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.
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. SWQ Ops plays a critical role in this expansion, making it possible to scale safely and efficiently. The Safety Operations team within SWQ Ops owns the scale delivery of datasets and methodologies used to evaluate the Safety and performance of the driver as Waymo continues to scale. We are on the front lines of:
- De-risking New Deployments: Through meticulous triage of driving and simulated 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 Ojai.
- 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.
- 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.
- Data Flywheel: 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.
You will:
- Drive the strategy and technical implementation of decomposing complex safety triage workflows. Develop and apply advanced operational and ML techniques to enable automation, ensuring scalability as mileage and geographic operations expand.
- Serve as the subject matter expert for human-in-the-loop ML systems in the safety problem space. Define and refine requirements for generating high-quality, dense, and broad human feedback to optimize ML models performance.
- 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. Author and drive the adoption of foundational technical policies and standards, strategic roadmaps, and process blueprints that enable the organization to scale and support stakeholder needs.
- Advise senior stakeholders on the long-term technical strategy and operational capabilities of the organization, serving as a trusted partner for critical decisions.
You have:
- BS/BA degree or 7+ years of relevant work experience in AV Software Quality Operations / ML Operations
- Proven ability to manage complex, technical projects and experience working across technical partners (Product, Engineering, Data Science, Systems Engineering) to drive outcomes.
- 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:
- Undergraduate in technical degree preferred.
- Experience within A / V space.
- Competency in LLM / transformer models, and / or ML for robotics domain experience.
- Competency in SQL querying / data analysis.
- Experience working with offshore teams / multiple local operations hubs.
Please note that Waymo may not be able to employ remotely in all locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.
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
$190,000—$234,000 USD