Senior Product Manager, Applied AI, DeepMind
Deepmind
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At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
In this role, you will work to create the roadmaps between Google wide engagements, with a focus on Gemini quality across different product surface areas and modalities. You will own the cross-surface model quality strategy for the biggest Gemini customer-impacting issues, and define the product strategy for advancing our enterprise capabilities for GDM models. You will serve as connective tissue between GDM Research, Google, and external partners, ensuring the success of Gemini's capabilities for enterprise customers. You will operate with high autonomy in an ambiguous, fast-moving environment.
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.
Responsibilities
- Own the cross-surface model quality strategy for Gemini across Cloud products driving prioritization and faster resolution of customer-impacting issues.
- Translate real-world quality signals and capability gaps from enterprise engagements into upstream research priorities, and close the loop by shipping improved model capabilities back into Cloud surfaces.
- Act as the connective tissue between Google Deepmind (GDM) Research and Cloud to align on shared priorities.
- Define and drive real-world evaluation frameworks that measure enterprise agent performance beyond standard benchmarks, establishing the quality bar across surface areas.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in product management or a related technical role.
- 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc).
Preferred qualifications:
- MBA or advanced degree in a relevant technical or business field.
- Experience working in a technical role such as Software Engineering, Research Engineering, or Research Science.
- Experience with enterprise systems, cloud platforms, and AI deployments and shipping enterprise-grade Business-to-Business (B2B) or Software-as-a-Service (SaaS) products from concept to scale.
- Understanding of the Generative Artificial intelligence (AI)/Large Language Model (LLM) landscape, including model evaluations, model capabilities, prompt engineering, fine-tuning, and agentic architectures.
Summary
Manage cross-surface AI model quality strategy, coordinate research and product teams, and drive enterprise AI solutions.
Job title
Senior Product Manager, Applied AI, DeepMind
Experience level
8+ years
Industry
software
Location requirements
Remote work allowed in Mountain View, CA, or New York, NY.
Salary
The US base salary range for this full-time position is $256,000-$278,000 + bonus + equity + benefits.
Management role
No
Required skills
Preferred skills
Specializations
Structured locations inferred from the posting.
Mountain View, CA, USA
New York, NY, USA