GenAI Technical Engagement Strategy Lead, DeepMind

Job description

Minimum qualifications

Bachelor’s degree in Computer Science, Data Science, Machine Learning, Maths, Statistics, Law, Public Policy, Security, Safety, or equivalent practical experience. 10 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.

About the job The GenAI Technical Engagement team within DeepMind is responsible for translating complex technical model-development roadmaps to support frontier AI public policy and regulatory efforts, driving strategy with cross-functional partners at Google to advance actionable advocacy routes to harmonize public policy efforts with frontier model development and deployment. In this role, you will work at the intersection of research, engineering, public policy, regulatory, product, and operational teams to anticipate emerging regulations (such as those related to AI model development, training data, copyright, safety, and security) and harmonize them with the DeepMind’s technical and model roadmap.

As the technical subject matter expert, you will collaborate closely with public policy, regulatory, and frontier AI model development teams to identify key technical needs and goals, steer advocacy strategies early, co-design policy playbooks and develop external responses to emerging regulations in ways that meet Google’s model development and deployment objectives.