Senior Staff Software Engineer, Capacity Optimization

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. We are establishing a new team called SCORPIO (SimEval Capacity Operations, Resource Planning, Infrastructure Optimization). This team will be at the forefront of ensuring the efficient and effective use of Waymo's large-scale simulation compute, storage, and network resources. SCORPIO will develop the data-driven models, metrics, and processes to forecast demand, plan capacity, and optimize resource allocation, ultimately improving developer experience and maximizing return on infrastructure investments. You will: As the founding Senior Staff Engineer of the SCORPIO team, you will: Define the vision, strategy, and technical roadmap for data-driven capacity planning and resource optimization within Waymo's simulation environment. Lead the development and implementation of sophisticated forecasting models to predict demand for heterogeneous TI resources (CPU, GPU, Storage, Bandwidth, RAM) across various time horizons and simulation workflows. Design, build, and maintain robust capacity models, key metrics, and insightful dashboards to monitor resource utilization, identify current and future bottlenecks, and inform investment decisions. Develop and propose actionable strategies for resource optimization, cost management, and risk mitigation to senior leadership, finance, and engineering teams. Collaborate deeply with Simulation, Infrastructure, Finance, Product Management, and Engineering teams to understand demand drivers, usage patterns, system changes, and their impacts on resource needs. Spearhead the design and development of automated systems for demand management, quota allocation, and resource reassignment to enhance efficiency and responsiveness. Provide data-driven insights to influence the design of simulation products and user guidelines, promoting more efficient resource consumption patterns. Build and mentor a high-performing team, potentially including data scientists, business analysts, and software engineers. You have: PhD or Master's degree in Data Science, Statistics, Operations Research, Computer Science, Industrial Engineering, or a related quantitative field. 10+ years of experience in data science or quantitative analysis, with a significant focus on capacity planning, resource optimization, demand forecasting, or a closely related area. 5+ years of experience in a technical leadership role, with a proven track record of defining strategy, setting technical direction, and leading complex projects. Strong expertise in statistical modeling, time series analysis, and forecasting techniques (e.g., ARIMA, Exponential Smoothing, regression models). Demonstrated ability to work with large-scale, complex datasets and experience with distributed computing environments. Proficiency in Python or R, including common data science libraries (e.g., pandas, NumPy, SciPy, scikit-learn). Expertise in SQL and experience with data warehousing solutions (e.g., BigQuery, etc.). Exceptional communication and collaboration skills, with the ability to convey complex quantitative findings and recommendations clearly to diverse audiences, including executive leadership. We prefer: Direct experience in CapEx Engineering, Cloud Services Capacity Planning (e.g., AWS, GCP, Azure), or managing resources for large-scale compute/HPC infrastructure. Familiarity with simulation workloads, performance analysis, and distributed systems. Experience with financial modeling, cost-benefit analysis, and ROI calculations related to technical infrastructure. Experience building and deploying data pipelines and automation tools in a production environment. Experience hiring, growing, and nurturing a technical team. 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 $281,000 — $356,000 USD

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