GenAI Technical Engagement Lead, DeepMind

• 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.

• 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.