The Waymo Driver is performing well in more and more cities, with our scale rapidly accelerating. Our team’s job is to ensure that we can continue to evaluate safety and service quality across new cities and countries, each with their unique challenges. We need an experienced, technically hands-on engineering manager with strong quantitative skills to lead a small team and work with partners to scale eval and ML development by exploring new methods and delivering tools for mining and sampling data.

In this hybrid role, you will report to the Sr. Staff Manager. 

You will:

• Lead the technical design and development of high-performance data platforms tailored for large-scale evaluation of autonomous driving software.
• Define long-term technical strategy and multi-year roadmaps, transforming ambiguous product requirements into concrete, high-impact engineering deliverables.
• Architect systems for data set curation, sampling, and slicing, ensuring that our evaluation pipelines are both representative of real-world complexity and computationally efficient.
• Manage a medium size team (5-7) of junior and senior SWEs, organizing them into effective workgroups with clear missions, projects, and APIs.
• Drive cross-functional execution, collaborating with Research, Product, and Safety teams to enable rigorous data-driven decision-making for behavioral evaluation.

You have:

• PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.
• Extensive experience in backend or infrastructure engineering, specifically building large-scale distributed systems or data processing platforms.
• A proven track record of technical leadership, having successfully led complex projects from initial concept through global deployment.
• Expertise in data modeling and systems design, with the ability to optimize for high-throughput data retrieval and analysis.
• Proven experience in people management, with a track record of developing junior engineers and mentoring high-performers.
• Strong proficiency in C++ or Python, along with experience in cloud infrastructure and big data technologies (e.g., MapReduce, Spanner, or similar).
• Exceptional communication skills, with a demonstrated ability to influence technical direction across multiple teams and stakeholders.

We prefer:

• Experience in the Autonomous Vehicle (AV) industry, particularly in areas related to simulation, evaluation, or machine learning infrastructure.
• Advanced degrees (Masters or PhD) in Computer Science, Robotics, or a related quantitative field.
• Familiarity with data visualization and analytics tools that help translate raw engineering metrics into actionable safety insights.
• A passion for safety-critical systems and the desire to solve the "long tail" of challenges inherent in autonomous driving.