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. As an engineer on the Gemini App Personalization team, you will build the next-generation personal AI assistant using Google’s Gemini models. Personalization is a top company priority, and we are continually building and launching personalized features across all Gemini App surfaces, including web, mobile, and Live. Our team is developing new personalization capabilities, such as understanding, contextualizing, and appropriately utilizing relevant personal information in responses and tool invocations. This work includes a different set of tasks: model post-training, evaluation, data retrieval and summarization, benchmark creation, data collection and synthesis, model serving, and production deployment.

Demonstrate leadership in AI-driven design and development, and leverage AI across the full product cycle and act as primary owner and critical judge of model output quality for specific personalization features.

Design, prototype, and build robust, scalable, user-facing personalization features on the full Gemini App stack.

Perform relevant data analysis of user feedback, logs, and evaluation tasks to identify personalization-related quality issues and opportunities.

Develop robust evaluation techniques (both automated and with a human in the loop) to assess and hill-climb on personalization quality.

Partner closely with Research Scientists, Engineers and cross-functional partners (product and program managers) to advance the business goals of the organization.

Lead technical working groups with engineers and research scientists to deliver quality improvements for users of the product.