Product Counsel, Gemini Models, DeepMind
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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 DeepMind’s mission and help achieve it.
- Ability to be curious and organized, maintain a sense of ownership, and act as a team player.
About the job
Google DeepMind is looking for an adept and enthusiastic Product Counsel for the Gemini model family.In this role, you will be a business advisor who partners with the Product and Research teams to advise on legal matters relevant to developing and releasing Gemini models, products, and systems.
You will also work with cross-functional teams to ensure we are prepared for forthcoming regulatory, policy, and legal changes that might impact our technology. Finally, you will 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.
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 several DeepMind Research and Engineering teams who you will partner with to develop and align models that are part of the Gemini model family or related model families.
- Monitor and interpret emerging regulations, laws, and commitments that impact the development and release of Gemini models.
- Advise executive management on risks associated with AI research direction and existing governance frameworks. Present creative, flexible options to mitigate or eliminate those risks at scale.
- Collaborate with and advise cross-functional groups within DeepMind, including Research, Engineering, Product Management, Security, Privacy, Responsibility, and Compliance teams to improve or establish governance frameworks for forthcoming regulatory or legal changes that impact model lifecycles.
- Establish practical governance frameworks for Gemini model development, including for training and alignment, evaluations, new capabilities, research, data, and other assets.
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