Our Simulation team is at the heart of this mission, enabling us to safely and rapidly iterate on the Waymo Driver. We run billions of miles of simulations, creating a massive and complex demand for technical infrastructure resources (CPU, GPU, TPU, Storage).

We are establishing a new team called SCORPIO (SimEval Capacity Operations, Resource Planning, Infrastructure Optimization). This team is tasked with building a critical capability for Waymo: data-driven, strategic capacity planning and resource optimization. We are looking for a Quant Software Engineer at the L6 level to bridge the gap between sophisticated mathematical modeling and production-scale infrastructure automation. You will be responsible for building the technical systems that forecast demand, optimize resource allocation, and automate infrastructure management, ensuring our simulation environment is both high-performance and cost-effective.

You will:

As the founding Lead Data Scientist of the SCORPIO team, you will:

• Infrastructure Modeling & Automation: Design and build production-grade systems and pipelines to automate capacity planning, demand management, and quota allocation.
• Quantitative Forecasting: Implement and maintain sophisticated models for infrastructure demand forecasting, incorporating architectural shifts, peak loads, and time-shifting opportunities.
• Resource Optimization Algorithms: Develop and deploy algorithms to optimize resource utilization across a heterogeneous fleet (CPU, GPU, TPU) and diverse supply models (on-demand vs. reserved).
• Data Pipeline Engineering: Architect and maintain robust data pipelines that ingest infrastructure telemetry and demand driver signals to feed forecasting and optimization engines.
• Outcome Analysis: Build systems to translate resource plans into tangible outcomes (e.g., queue lengths, user demand fulfillment) and develop attribution models for capacity imbalances.
• Cross-Functional Collaboration: Partner with Simulation, Infrastructure, and Finance teams to translate business requirements into technical specifications and automated solutions.
• Technical Leadership: Provide technical guidance on the intersection of quantitative modeling and systems engineering, mentoring junior members and influencing the technical roadmap for SCORPIO.

You have:

• Bachelor's degree in Computer Science, Mathematics, Statistics, Operations Research, or a related quantitative field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on distributed systems, large-scale data processing, or quantitative engineering.
• Proficiency in C++ or Python, with experience building and deploying production-level software.
• Experience with large-scale distributed systems and cloud infrastructure (e.g., GCP, AWS, Azure).
• Strong background in quantitative methods, such as optimization, statistical modeling, or time-series analysis.
• Expertise in SQL and working with large-scale data warehouses (e.g., BigQuery).

We prefer:

• PhD or Master's degree in a quantitative field or Computer Science.
• Experience in Capacity Engineering, Infrastructure Optimization, or Site Reliability Engineering at scale.
• Familiarity with ML-driven forecasting and optimization techniques.
• Experience with financial modeling or cost-benefit analysis of technical infrastructure.
• Experience building automation tools for resource management and quota allocation.
• Knowledge of simulation workloads or high-performance computing (HPC) environments.