Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in product management.
• Experience in machine learning, AI, or a related technical field.
• Experience driving product vision, go-to-market strategy, and design discussions.

Preferred qualifications:

• Experience in non-traditional field such as philosophy, cognitive science, human-computer interaction (HCI), or linguistics.
• Experience working on products related to natural language processing (NLP), large language models (LLMs), or generative AI.
• Experience in consumer-facing products where user experience and engagement are critical.
• Experience working closely with research and engineering teams on highly technical and ambiguous problems.

About the job

As a Product Manager for Persona and Behavior, you will define the core rulebook for Gemini's default behaviors and navigate the subjective, complex trade-offs of how our models should act in creative, ambiguous, and novel scenarios. You will be responsible for outlining what “good” looks like for Gemini, working to balance the model’s "IQ and EQ" and defining its expressive range. You will work closely with our research, engineering, and post-training teams to bring our model’s personality to life.

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

• Define and maintain the model specification, the core rulebook that governs Gemini's default behaviors, personality, and interaction style.
• Lead the product goal for model personality, balancing the IQ and EQ to define the expressive range and character of our models.
• Collaborate with Engineering, UX/Design, Research, and Trust and Safety teams to navigate the subjective trade-offs of how the model should behave in ambiguous scenarios.
• Develop frameworks and methodologies for evaluating model quality from a taste perspective, working on agent evaluations to outline what “good” looks like.
• Partner with post-training teams to implement and refine the model’s personality and style, ensuring it aligns with our product goals and constitutional AI principles.