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.
Responsibilities
Work to develop novel and practical solutions for AI and AI-powered tools.
Work on ambiguous, ill-defined problems, move quickly, iterate rapidly, and handle complex problems and codebases.
Develop a wide range of solutions, spanning from frontend to backend infrastructure (e.g., effective UI, storing new knowledge, all kinds of tools used by LLM, efficiently using LLMs to evaluate thousands of requests, improving those models, and enhancing their intelligence).
Work in the context of real applications for important Google products and in partnership with product teams and other research engineers.
Balance rapid, exploratory prototyping with the discipline to write clean, scalable code.
Qualifications
Minimum
Bachelor's degree in Computer Science, Artificial Intelligence, a related field, or equivalent practical experience.
5 years of experience with full stack development, across back-end such as Java, Python, or C++ codebases.
Experience working with cross-functional teams and collaborating across internal and external teams.
Experience in front-end and JavaScript or TypeScript, HTML, CSS or equivalent.
Experience in UI design.
Preferred
Experience with Generative AI and Generative AI Agents.
Ability to solve real problems, overcome obstacles, and work any task to get the job done.
Exceptional hacking skills and ability to quickly prototype and iterate on complex systems.
Quick learner with strong analytical skills and willingness to learn multiple tools and codebases.
Willingness to work on ambiguous problems, refining goals as new information is learned.
Track record of solving exceptionally complex problems (e.g., math/programming competitions or novel algorithms).