Job Description

The RO Performance team is at the heart of understanding and improving Waymo's self-driving technology. We build and maintain the critical infrastructure, to process and analyze vast amounts of data from both real-world driving logs and simulations.

Our systems generate key metrics and power dashboards which are essential for tracking the product performance, identifying areas for improvement, and making data-driven decisions. The insights produced by our team directly influence Waymo's operational rollouts, weekly performance reviews, and ultimately, the safety and reliability of our autonomous vehicles.

In this hybrid role, you will report to an Staff Software Engineer.

You will:

• Infrastructure & Pipeline Engineering: Design and operate high-performance, low-latency data pipelines for both massive-scale simulation and real-world monitoring.
• Evaluation Fidelity: Improve the signal quality of driving tests by ensuring simulation results are highly predictive of real-world behavior and implementing metrics to measure simulation accuracy.
• ML Integration: Deploy and potentially contribute to ML models that identify "interesting" driving scenarios, optimizing the efficiency of testing through robust integrations with large-scale models.
• Software Excellence: Champion code health and developer experience by applying best practices to the simulation and monitoring ecosystems.
• Cross-Functional Collaboration: Partner with Data Scientists and Systems Engineers to translate complex vehicle telemetry into actionable insights regarding the Waymo Driver's internal logic.

You have:

• 5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience
• C++ (or another OOP language) proficiency
• Python familiarity
• SQL familiarity
• Excited about autonomous driving, Simulation + Eval

We prefer:

• 7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality- focused engineering role in which you had experience as a technical lead for a team in which you were performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long term stability and health of the production system.
• B.Sc., M.Sc. or PhD in Computer Science
• Experience working with large FAANG scale distributed systems.