GenAI Technical Engagement Lead, DeepMind

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 model development lifecycles, model capabilities, training data architectures, and model evaluation and deployment.
• Experience working with cross-functional teams in technical engineering or 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 on issues central to AI model development, including data use, model architecture, safety, security, and compute.
• Track record of strong contributions to AI model development as a technologist, researcher, public policy manager, or communications specialist.

About the job

The GenAI Technical Engagement team translates complex technical model-development roadmaps to support frontier AI public policy and regulatory efforts. The role works collaboratively with cross-functional partners to advance actionable advocacy approaches that align public policy efforts with frontier model development and deployment.

You will work across research, engineering, public policy, regulatory, product, and operations teams to anticipate emerging regulations related to AI model development, training data, copyright, safety, and security, and align them with technical and model roadmaps.

As a technical subject matter expert, you will collaborate with public policy, regulatory, and frontier AI model-development teams to identify technical needs and goals, guide advocacy strategies early, co-design policy playbooks, and develop external responses to emerging regulations that support model development and deployment objectives.

Responsibilities

• Bridge AI development and regulation by translating complex AI model-development plans into actionable public policy responses co-designed with internal teams.
• Steer cross-functional advocacy by partnering with teams managing public policy responses so advocacy frameworks and playbooks evolve alongside model-development roadmaps.
• Advise senior management on emerging regulatory developments, their impact, and recommended solutions based on model-development plans.
• Serve as a technical subject matter expert for policy and regulatory teams, guiding internal teams and public policymakers on AI topics such as training-data disclosures and model transparency.
• Establish metrics to measure the success and impact of advocacy campaigns on the model-development roadmap and generate insights to optimize campaigns.