Software Engineer, AI System Hacker, Genai, Deepmind

Google Google · Big Tech · Mountain View, CA +1

Software Engineer role at Google DeepMind focused on building and testing AI agents. Responsibilities include developing agent testing systems, creating test problems in simulators, visualizing results, building leaderboards, and testing algorithms on robots. The role involves working on both frontend and backend infrastructure for AI tools, improving LLMs, and integrating AI into Google products. Requires strong software engineering skills and experience with Generative AI Agents.

What you'd actually do

  1. Work to develop novel and practical solutions for AI and AI-powered tools.
  2. 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).
  3. Work in the context of real applications for important Google products and in partnership with product teams and other research engineers.
  4. Balance rapid, exploratory prototyping with the discipline to write clean, scalable code.

Skills

Required

  • full stack development
  • backend development (Java, Python, or C++)
  • cross-functional team collaboration
  • frontend development (JavaScript, TypeScript, HTML, CSS)
  • UI design

Nice to have

  • Generative AI
  • Generative AI Agents
  • solving complex problems
  • prototyping and iteration
  • analytical skills
  • learning multiple tools and codebases
  • working on ambiguous problems
  • experience with 2D and 3D games for agent testing
  • experience with physics simulators for test problems
  • experience with robotics

What the JD emphasized

  • complex task of measuring the intelligence of our prototypes
  • creating systems for agent testing
  • developing test problems within physics simulators
  • build competitive agent leaderboards
  • test new algorithms on robots
  • strong foundation in software engineering
  • wide range of challenging problems
  • mission-driven team
  • pioneering AI lab
  • advancing AI development
  • solve complex global challenges
  • accelerate high-quality product innovation
  • widespread public benefit
  • scientific discovery
  • safety and ethics are always our highest priority
  • pushing the boundaries across multiple domains
  • diverse learning opportunities
  • varied career pathways
  • driven to achieve exceptional results
  • collective effort
  • novel and practical solutions for AI and AI-powered tools
  • ambiguous, ill-defined problems
  • move quickly
  • iterate rapidly
  • handle complex problems and codebases
  • wide range of solutions
  • frontend to backend infrastructure
  • effective UI
  • storing new knowledge
  • all kinds of tools used by LLM
  • efficiently using LLMs to evaluate thousands of requests
  • improving those models
  • enhancing their intelligence
  • real applications for important Google products
  • partnership with product teams
  • other research engineers
  • Balance rapid, exploratory prototyping
  • discipline to write clean, scalable code
  • Generative AI and Generative AI Agents
  • solve real problems
  • overcome obstacles
  • work any task to get the job done
  • Quick learner
  • strong analytical skills
  • 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
  • math/programming competitions
  • novel algorithms

Other signals

  • developing systems for agent testing
  • developing test problems within physics simulators
  • building competitive agent leaderboards
  • testing new algorithms on robots
  • developing novel and practical solutions for AI and AI-powered tools
  • developing a wide range of solutions, spanning from frontend to backend infrastructure
  • storing new knowledge
  • all kinds of tools used by LLM
  • efficiently using LLMs to evaluate thousands of requests
  • improving those models
  • enhancing their intelligence
  • working in the context of real applications for important Google products
  • partnership with product teams and other research engineers
  • balance rapid, exploratory prototyping with the discipline to write clean, scalable code
  • experience with Generative AI and Generative AI Agents
  • exceptional hacking skills and ability to quickly prototype and iterate on complex systems
  • track record of solving exceptionally complex problems