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 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 learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $256000 - $279000 (USD) + 20% bonus target + bonus + equity + benefits
Learn more about
benefits at Google.
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.