GDM Staff Software Engineer, Agent Data Quality

About the role

MINIMUM QUALIFICATIONS:

• Bachelor's degree in Computer Science or Engineering, or equivalent practical

experience.

• Experience with Large Language Models (LLMs), NLP, or Generative AI.

PREFERRED QUALIFICATIONS:

• MBA or Master's degree in Computer Science.

ABOUT THE JOB:

At Google DeepMind our mission is to build the world's first general-purpose

learning agent. Central to this mission is the complex task of measuring the

intelligence of our prototypes. As a Software Engineer, you will be working with

the cutting edge AI agents developed by our exceptional team of Machine Learning

and Neuroscience research scientists. Your responsibilities will include

everything from creating systems for agent testing using 2D and 3D games to

developing test problems within physics simulators. You will create graphical

visualization of results, build competitive agent leaderboards and test new

algorithms on robots. To succeed in this role you will need to have a strong

foundation in software engineering and enjoy working on a wide range of

challenging problems within a mission-driven team.

Artificial intelligence will be one of humanity’s most transformative

inventions. At Google DeepMind, we are a pioneering AI lab with exceptional

interdisciplinary teams focused on advancing AI development to solve complex

global challenges and accelerate high-quality product innovation for billions of

users. We use our technologies for widespread public benefit and scientific

discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer

diverse learning opportunities and varied career pathways for those driven to

achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Construct rigorous quantitative benchmarks and automated evaluation

frameworks (including LLM-as-a-judge) to measure agent capabilities in

reasoning, planning, and tool use.

• Develop end-to-end data flywheel on agent evalset curation, and automate and

productionize the flywheel with agentic data pipelines.

• Develop a dedicated platform for "Self-Service Judges," allowing researchers

to rapidly prototype and test new LLM-based classifiers and annotations

against historical trajectory data.

• Establish a formal ecosystem for metric lifecycle management, including a

sandbox for validating new metrics against a library of high-confidence

calibration experiments.

• Productionize automated insights tools to identify the top movers of metric

deltas across complex slices such as task type and user cohort.