Minimum qualifications:

• Bachelor's degree in Technology, Business, or a related field, or equivalent practical experience.
• 10 years of experience in a business function or role (e.g., marketing, business operations, consulting).
• 7 years of experience working cross-functionally with engineering, research, and other stakeholders.
• 5 years of experience in a role preparing and delivering technical presentations to executive leadership.
• 5 years of experience in software development or engineering.

Preferred qualifications:

• Experience with advanced AI, LLMs (fine-tuning, agent harnesses), generative image, video, and audio models, and technical software development to build products and collaborate with engineering.
• Expertise designing evaluation methods, model success metrics, safety protocols, and adversarial analysis to effectively address ethical risks and drive continuous product enhancements.
• Proven ability to independently drive complex, ambiguous product initiatives, collaborating cross-functionally with engineering, legal, and GTM partners to deliver results.
• Strong user-centric focus to identify pain points and build intuitive AI experiences, with demonstrated ability to deliver compelling technical presentations to executive leadership and external customers.

About the job

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.

As a Product Manager for DeepMind’s Applied AI team, you will bridge the gap between AI research and real-world enterprise impact, focusing specifically on image, video, and audio applications in media and entertainment. In this role, you will partner with clients, Research Engineers, and cross-functional teams to identify, scope, and deploy frontier AI solutions. This involves constructing technical solutions, conducting model evaluations, and managing complex engagements from early discovery to final delivery. You will define and lead the product goal, strategically integrating generative AI capabilities in a rapidly evolving landscape. You will grow in ambiguous environments, be passionate about advancing human-AI interaction, and translate subtle user needs into intuitive AI solutions.

Artificial intelligence will be one of humanity’s most transformative inventions. At 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

• Drive engagement progress programmatically and technically, focusing on developing model evaluations, identifying loss patterns, and transforming data to test hypotheses.
• Manage various stakeholders, including DeepMind Research Engineers for technical delivery, clients for project execution, and cross-functional teams (GTM, legal, partnerships) to ensure firm engagement foundations.
• Analyze the enterprise AI landscape, market trends, and engaged offerings to identify opportunities and threats for Google's AI products.
• Maintain deep technical expertise in advanced AI to intuitively understand and predict emerging model capabilities.