Research Scientist, Gemini Personal Intelligence

DeepMind • Mountain View, CA

1d

About The Position

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. About Us Our team drives the Personal Intelligence research behind Gemini, with a mission to make AI more personal, proactive, and context-aware. You will push the boundaries of Large Language Models (LLMs) to build the brain of the world’s most helpful personal assistant—one that securely integrates with users' personal data to solve real-world problems. Our core research focus areas include: Personalization: Inferring and adapting to user intent, preferences, communication styles, etc. Context: Reasoning over extensive personal history (e.g., Gmail, Photos, Drive) across diverse modalities (Text, Image, Audio, Video). Agency: Empowering AI models to autonomously plan, use tools, and execute complex tasks on behalf of the user. The Role As a Research Scientist for Gemini Personal Intelligence, you will advance the state-of-the-art in understanding and reasoning to create an AI that truly understands, remembers, and adapts to the user's unique life and context.

Requirements

• PhD in Machine Learning, Computer Science, or a relevant field (or equivalent practical research experience).
• A proven track record of research excellence (e.g., publications at top-tier venues like NeurIPS, ICML, ICLR, or significant industry contributions), ranging from recent graduates to experienced researchers.
• Strong software engineering skills to complement your research background.

Nice To Haves

• Hands-on experience with modern post-training methods (SFT, RLHF, etc.).
• Prior work applying LLMs to personalization, memory, or agentic workflows.

Responsibilities

• Driving research on post-training techniques (e.g., RL, SFT, and preference optimization) specifically tailored for personalization scenarios.
• Developing novel evaluation frameworks and simulation methods to measure model quality against user behaviors / feedback.
• Designing and training agents capable of orchestrating tools and APIs to deliver hyper-personalized experiences.

Benefits

• enhanced maternity, paternity, adoption, and shared parental leave
• private medical and dental insurance for yourself and any dependents
• flexible working options
• healthy food
• an on-site gym
• faith rooms
• terraces
• relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree