GenAI Technical Engagement Lead, DeepMind
Summary
A technical liaison role at Google DeepMind translating frontier AI model-development roadmaps into public policy and regulatory advocacy, advising senior management, and serving as a technical expert on topics like training data and model transparency. Requires deep familiarity with foundational model lifecycles and cross-functional work across research, policy, and engineering.
We are pushing the boundaries across multiple domains. Our global teams offer varied learning opportunities and 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: $277000 - $308000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
- Bridge the gap between AI development and regulation by translating complex AI model development plans into actionable public policy responses that you co-design with Google teams.
- Lead cross-functional advocacy by partnering directly with Google cross-functional teams who are managing public policy responses to ensure advocacy and policy frameworks and playbooks evolve in lockstep with model development roadmaps.
- Advise senior management on the status of emerging, novel regulatory developments, including impact, and recommended solutions based on model development plans.
- Serve as a technical subject matter expert for policy and regulatory teams, providing guidance to internal teams and public policymakers on AI concepts such as training data disclosures and model transparency.
- Establish metrics to measure the success and impact of advocacy campaigns on model development roadmap, generating actionable insights for campaign optimization.
Minimum qualifications:
- Bachelor’s degree in Computer Science, Data Science, Machine Learning, Law, Public Policy or equivalent practical experience.
- 8 years of experience in either technical product/engineering/researcher roles, or policy/regulatory-facing roles.
- Experience with foundational models development life-cycles, model capabilities, training data architectures, and model evaluation and deployment.
- Experience working with cross-functional teams in technical engineering/research organizations.
Preferred qualifications:
- Advanced degree in a technical discipline or public policy.
- Experience designing, leading, or implementing high-stakes, complex projects from the ground up.
- Experience engaging with regulators and policymakers about the issues at the heart of AI model development, including data use, model architecture, safety, security, and compute.
- Track record of excellent contributions to AI model development as a technologist, researcher, public policy manager, or communications specialist.