Jobs at Waymo

Provides legal counsel for Waymo’s Canadian operations, advising on negotiations, advocacy, disputes, regulatory changes, compliance, governance, and business strategy. The role partners with public policy, regulatory, product, communications, and operations teams; engages Canadian regulators and authorities; supports global legal initiatives; and develops expertise in emerging Canadian legal issues affecting autonomous driving and ride-hailing services.

Lead growth marketing strategy for Waymo’s autonomous ride-hailing business, driving U.S. market launches, product adoption, use-case expansion, loyalty, customer engagement, and retention. Build and guide a high-performing team, develop segmentation and growth plans, collaborate cross-functionally, and establish measurement frameworks to evaluate investments and deliver measurable business outcomes.

Design and implement multimodal, multitask perception models for autonomous driving, including object detection, tracking, segmentation, occupancy detection, and foundation models. Train and evaluate machine learning models using large-scale Waymo driving data and infrastructure. Collaborate with technical teams while gaining experience in production-scale machine learning systems.

Lead Waymo’s Singapore go-to-market strategy and business operations. Responsibilities include market and competitive analysis, quantitative modeling, KPI development, cross-functional initiative leadership, international market scaling, stakeholder coordination, and engagement with government and strategic partners. The role serves as a bridge between Singapore and global teams, helps establish local processes, supports regulatory and policy considerations, and drives strategic decisions for commercial deployment.

Develop and productionize agentic systems that accelerate release qualification, improve developer velocity, and automate test development and execution. Work across frontend, backend, multiple programming languages, and large software systems while creating novel automation solutions. The role involves systems thinking, experimentation, and collaboration on robotics, firmware, hardware-in-the-loop, test engineering, release management, and AI-backed products.

Build and own production machine learning infrastructure for growth initiatives, including feature pipelines, point-in-time-correct training data, batch inference, model registries, retraining automation, validation safeguards, and production monitoring. Partner closely with data science and data engineering to productionize models, prevent data leakage and train-serve skew, and ensure reliable model-driven promotions.

Prepare month‑end and quarter‑end close deliverables, financial statements, flux analysis, and reporting packages; design operational processes and controls; lead automations and systems implementations; perform technical accounting research and documentation; collaborate with FP&A, Legal, AP, and Systems teams.

Develop high-performance GPU primitives, abstractions, profiling and debugging tools for autonomous vehicle compute platforms. Collaborate on GPU-focused SoC projects, bring up and optimize onboard software across new GPU platforms, and improve GPU testing and CI/CD infrastructure. The role requires strong C++ and CUDA expertise, GPU software and hardware knowledge, and performance analysis skills.

Develop controllable, realistic adversarial agents for simulation-based autonomous-driving evaluation and deploy them in the Waymo Simulator. Improve post-training recipes for foundation and world models. The internship requires pursuing a PhD in computer science, machine learning, robotics, or a related field, with proficiency in Python, tensor manipulation, machine learning, and deep learning. Experience with reinforcement learning, diffusion or autoregressive architectures, attention mechanisms, autonomous driving, or robotics is preferred.

Own the roadmap for machine-learning-powered pickup and dropoff features. Train, evaluate, and deploy models for occupancy detection, rider interactions, pullover selection, and lost-and-found. Design onboard/offboard fallback systems, build distributed vehicle-to-cloud services, integrate end-to-end user-facing features, and measure impact through metrics, simulation, offline evaluation, and live experiments.

Drive cross-functional execution of autonomous vehicle expansion testing and validation across domestic and international markets. Coordinate fleet setup, driving configurations, market-entry roadmaps, milestones, launch readiness, reporting, and program reviews. Establish processes, tooling improvements, and operational playbooks while managing risks and aligning Product, Engineering, Operations, and Mapping teams.

Develop and execute communications strategies for Waymo product and technology announcements. Translate complex engineering topics into accessible stories, support executive spokespeople, manage media relationships, pitch reporters, respond to emerging issues, and write press releases, blog posts, technical explainers, and social content. The role requires extensive communications experience, strong media relations, technical storytelling ability, launch management skills, and sound judgment when working with Legal, Safety, Engineering, and Product teams.

The role involves executing administrative functions, managing executives' schedules, leading projects, and collaborating effectively with diverse teams.

Develop and deploy next-generation sensor calibration systems for autonomous vehicles. Responsibilities include scaling calibration algorithms across hardware architectures, evaluating ML-based calibration approaches, and collaborating with hardware, software, and operations teams to deploy robotic systems. The role requires graduate study in computer science, robotics, or a related technical field and C++ experience.

Performs month-end revenue accounting, analyzes and operationalizes revenue offerings and market launches, supports revenue and order-to-cash ERP implementations, and automates accounting processes. Partners with cross-functional stakeholders and serves as the accounting subject-matter expert for system enhancements and new business processes.

Develop and implement operational systems that standardize work, improve processes, reduce variability and cost, and strengthen operational excellence across Waymo Operations. Lead complex cross-functional improvement initiatives, facilitate problem solving, establish corrective actions and standards, coach teams on efficiency, and advise organizational leaders. The role requires driving process maturity, workflow optimization, quality systems, and continuous improvement in safety-critical autonomous vehicle operations.

Develops autonomous-driving simulation technology at Waymo. Responsibilities include analyzing simulator performance, identifying gaps, documenting findings, collaborating with stakeholders, and developing simulator functionality through clean APIs. The internship targets master's and PhD students with software engineering, evaluation, and API design experience, preferably involving autonomous simulation, distributed computing, data pipelines, rendering engines, and exploratory research.

Build and enhance Waymo’s ML Datagen Controlplane, an infrastructure system for orchestrating, prioritizing, and tracking data-generation requests. Translate requirements into designs, develop large-scale datagen functionality in C++, expand UI and visualization capabilities, and test and debug systems and pipelines. Collaborate with ML Ops team members and internal customers while gaining experience in autonomous-driving software engineering.

Lead a team developing software metrics and evaluation systems for autonomous-driving quality. Define strategy and roadmaps, analyze simulation and real-world driving data, improve code health, and collaborate with engineers, data scientists, statisticians, and leadership to deliver data-driven evaluation products.

Manages imagery-focused mapping operations, including vendor coordination, mapping tool and workflow rollouts, operational efficiency improvements, data anomaly investigation, technical documentation, and policy/SOP development. Partners with engineering teams to resolve blockers and maintain pipeline throughput and quality. The role may also involve geospatial data, HD maps, GIS, LiDAR, sensor data, SQL, and Python.