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Lead reliability strategy and execution for Waymo’s critical release pipelines. Drive incident response, retrospectives, disaster recovery, capacity planning, observability, and continuous improvement. Harden production software, develop playbooks, improve on-call metrics, investigate novel events, and contribute to robust, debuggable system architecture. Partner across engineering organizations to promote reliability practices for large-scale autonomous vehicle software systems.

Design autonomous vehicle test metrics, plans, and simulated scenarios for off-nominal situations; build dashboards analyzing fleet-wide fault rates; support verification and validation of fault-protection and remote-assistance behaviors; and develop Python and SQL pipelines to maintain and validate safety-critical test coverage.

Manage global brand marketing operations, including cross-functional go-to-market processes, campaign execution, agency coordination, scheduling, workflow documentation, billing, budget forecasting, and scalable frameworks for expansion into additional markets. Coordinate media, advertising operations, creative, and external agency stakeholders to deliver campaigns on time and support high-complexity team programs.

The Market Operations Lead will oversee the operational performance of the Ride-hail services, ensuring quality, scalability, and reliability while leading cross-functional teams in the Bay Area.

Develop and verify depot and off-hail automation features for autonomous vehicle fleets. Responsibilities include defining requirements and system architecture, building verification and monitoring systems, qualifying new features and depots, debugging field issues, improving test coverage, and extending automation across vehicle platforms. The role requires cross-functional collaboration, data-driven problem solving, C++ code analysis, SQL querying, and dashboard creation.

Leads public policy strategy, legislative advocacy, and regulatory engagement across the San Francisco Bay Area. Builds relationships with local elected officials, transportation agencies, civic leaders, and community groups; tracks municipal policy initiatives; develops policy positions; represents Waymo at public meetings and industry coalitions; and collaborates with public affairs, operations, communications, and safety teams.

Lead end-to-end actuarial analyses, including data preparation, commercial auto pricing, reserving, risk modeling, and actionable presentations. Build scalable data pipelines using R, Python, and SQL; automate workflows with AI and modern analytical tools; quantify autonomous driving risks; and collaborate with Safety, Engineering, Product, Legal, and Finance. Establish modeling standards, document processes, and mentor teammates while supporting insurance and risk-financing strategies.

Architect, train, and optimize multimodal deep learning models for autonomous vehicle perception. Build large-scale data mining, active learning, hard-example curation, and auto-labeling pipelines. Develop high-resolution vision and spatial-temporal transformer architectures, use foundation models for data curation and synthetic edge cases, and optimize models for onboard accelerator inference.

Leads global product marketing strategy for Waymo’s autonomous ride-hailing products, including positioning, launches, market expansions, adoption, and growth. Partners with Product, Engineering, and Operations leadership to influence roadmaps and business priorities. Synthesizes consumer, brand, competitive, product, and business insights to guide market decisions. Builds and develops a high-performing global Product Marketing team and supports U.S. and international market health.

Develop, evaluate, and release learned driving policies for autonomous vehicles, particularly complex navigation and yielding scenarios. Bridge multimodal perception and planning outputs into safe behavioral actions, evaluate models in closed-loop simulation against safety metrics, and transition production-ready models into autonomous navigation systems. The role also advances data-driven policies, foundation-model experimentation, scenario generation, and end-to-end driving architectures.