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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; London, UK.
Minimum qualifications: - PhD degree in programming languages, formal methods, or a related area, or equivalent practical experience.
- 4 years of experience with real-world software verification and bug-finding.
- 3 years of experience with proof assistants (Lean, Rocq, or similar) or SMT-solvers.
Preferred qualifications: - Experience with formalizing the semantics of real-world languages.
- Track record of publications at top computer science venues.
About the jobArtificial 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 various 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: $174000 - $252000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Develop and improve AI agents that generate formally verified code, algorithms, and mathematical proofs using the Lean proof assistant.
- Formalize the semantics of programming languages (e.g., C/C ) in Lean and build verified static analyses on top of these formalizations.
- Design and run experiments evaluating AI-driven proof search, including benchmarking against open problems in mathematics and real-world codebases.
- Build infrastructure for applying formal verification at scale, translating code, orchestrating proof search, and integrating with Google-internal tools and models.
