Minimum qualifications:
- JD, LL.B., equivalent degree, or equivalent practical experience.
- 7 years of attorney-level experience in government, in-house, or at a law firm.
- Experience in partnering with executives on legal matters.
- Experience advising on legal and regulatory frameworks relevant to the full model lifecycle, as well as general privacy and consumer protection regulations ( e.g., EU AI Act, GDPR, CCPA, Digital Markets Act).
- Admitted to the bar and in good standing or otherwise authorized to practice law (e.g., have registered in-house status) in the state in which the position is located.
Preferred qualifications:
- Experience in legal contributions to AI model development as in-house legal counsel at a technology company.
- Understanding of opportunities and risks of AI models and systems.
- Understanding of modern generative AI model classes.
- Understanding of key legal and business issues AI providers face and how to build models accordingly.
- Understanding of Google DeepMind’s mission and help achieve it.
- Ability to be curious and organized, maintain a sense of ownership, and act as a team player.
Experience in legal contributions to AI model development as in-house legal counsel at a technology company.Experience in legal contributions to AI model development as in-house legal counsel at a technology company.
About the job
The Google DeepMind Legal team is looking for an adept and enthusiastic product counsel to partner with the data engineering, product, and research teams to advise them on legal matters relevant to developing an exceptional data strategy.
Data strategy is a key component in developing the AI models, products, systems, and technology. You will be a business advisor who works with cross-functional teams to ensure we are prepared for forthcoming regulatory changes that might impact the data strategy. You will also collaborate closely with Google DeepMind compliance teams, other members of the legal team, Google Regulatory Affairs, and with outside counsel when needed.
You will be proactive, need exceptional communication skills, and know how to balance business demands (including legal, policy, technical, compliance, and cultural demands) to produce practical, solution-focused recommendations. You will do this while instilling trust in everyone you interact with.
Artificial 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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
The US base salary range for this full-time position is $344,000-$383,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.Data strategy is a key component in developing the AI models, products, systems, and technology. You will be a business advisor who works with cross-functional teams to ensure we are prepared for forthcoming regulatory changes that might impact the data strategy. You will also collaborate closely with Google DeepMind compliance teams, other members of the legal team, Google Regulatory Affairs, and with outside counsel when needed.
You will be proactive, need exceptional communication skills, and know how to balance business demands (including legal, policy, technical, compliance, and cultural demands) to produce practical, solution-focused recommendations. You will do this while instilling trust in everyone you interact with.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
The US base salary range for this full-time position is $344,000-$383,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.
Responsibilities
- Be the go-to counsel for the Data Engineering, Product and Research teams. Collaborate with Google cross-functional groups to support them.
- Become an expert on Google DeepMind data strategy, data governance, research, technology, and product needs. Anticipate and address regulatory, legal, policy, and other legal-adjacent risks that impact those needs.
- Collaborate with cross-functional teams, including Google Legal, Regulatory Affairs, Policy, and Compliance teams to propose, refine, and advance well-balanced regulatory and legal positions that take into account Google DeepMind data needs. Advise on the implications of those positions for Google DeepMind.
- Advise executive management on risks associated with the direction of data-related plans, and present options to mitigate or eliminate those risks.
- Advise technical executive management on how to translate and implement new and existing data regulations, commitments, and governance frameworks into actionable, technical requirements.
