Novel AI Lead Methodologist

About the job

Novel Testing is a team within Trust and Safety specializing in complex testing, defining protocols and methodologies for assessing risk where best practices do not currently exist. We pioneer and scale testing programs, streamlining the launch of trustworthy, novel AI products.

Work spans from designing first-of-their-kind evaluations for Google’s most ambitious product bets—including autonomous agents, personalization, and the latest hardware—to developing new methodologies for assessing novel foundational model capabilities as they emerge.

Advancing in AI evaluation is central to this mission. To scale these methods, we partner closely with engineering teams to build the infrastructure and tools required for automated evaluation.

In this role, you will lead the development of novel testing methodologies for emergent AI, designing evaluation frameworks where established standards do not yet exist. You will address complex testing questions with creative experimentation, designing sophisticated prompt strategies and quantitative analyses to identify systemic risks and edge cases in GenAI products.

Bridging the gap between theory and execution, you will move quickly to build and prototype testing solutions that incorporate methodological best practices. You will then partner directly with data science and engineering teams to inform the development of novel testing approaches and automated infrastructure, ensuring your insights scale effectively across Google’s ecosystem. This position demands a researcher’s mindset—capable of deep qualitative and quantitative inquiry—paired with the technical agility to translate those findings into scalable, engineering prototypes.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $171000 - $248000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Drive the methodological frontier of model evaluation. Partner with DeepMind and Data Science, developing novel, data-driven methodologies for structured and unstructured testing of emerging AI products. Move beyond standard benchmarks, designing sophisticated experimental frameworks, uncovering latent model behaviors and capabilities.
• Define testing and safety standards, working with cross-functional colleagues to ensure they are met. Perform analyses and drive insights to develop model-level and product-level safety mitigations.
• Lead and influence cross-functional teams to implement safety initiatives. Advise executive leadership on complex safety issues.
• Represent Google's AI safety efforts in external forums and collaborations, contributing to industry-wide best practices. Mentor analysts, fostering a culture of excellence, acting as a subject matter expert on adversarial techniques.
• Work with sensitive content or situations and may be exposed to graphic, controversial or upsetting topics or content.