Minimum qualifications:

• Bachelor's degree in Cognitive Science, Human-Computer Interaction (HCI), Linguistics, a related field, or equivalent practical experience.
• 6 years of experience in conversation design, content design, with equivalent experience designing for conversational AI/LLMs.
• include a portfolio, website, or any other relevant link to your work in your resume (providing a viewable link or access instructions).

Preferred qualifications:

• Experience in interaction design, particularly managing mixed tactile/voice entry points and mid-conversation modality switching.
• Experience in guiding cross-functional teams through ideation, validation, and iteration processes, transforming abstract ideas into shippable, user-centered model behavior.
• Experience in vibe-coding and developing AI-powered prototypes.
• Familiarity with behavioral data and strong capability to utilize user signals and lifecycle data to create data-driven designs, while being equally capable of moving forward in the absence of data.
• Excellent communication and collaboration skills with the ability to articulate positions, and challenge cross-functional partners with rigorous model UX principles.

About the job

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

• Specify the ideal conversational structures, query categorization logic, and underlying interaction patterns that bring voice, text, and multimodal entry points to life.
• Implement advanced system instructions (SIs) that optimize dynamic responses based on user signals and device capabilities.
• Apply systems thinking to deliver flexible solutions that scale across a range of devices.
• Initiate qualitative assessments of model performance, establishing principle-based rubrics to drive continuous quality hillclimbing across core user journeys (CUJs).
• Partner with AI product designers to craft leading-edge multimodal solutions, ensuring model responses, device signals, and screen relevancy work in concert to deliver cohesive, glanceable experiences.