JobPosting
title: Research Scientist, Gemini Safety
description: We're seeking a versatile Research Scientist to join our Gemini Safety team, responsible for advancing the safety and fairness behaviour of state-of-the-art AI models. As a key member of our team, you will apply and develop cutting-edge data and algorithmic solutions to ensure Gemini models are safe, maximally helpful, and work for everyone. Key responsibilities include: * Post-training/instruction tuning state-of-the-art language models, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities * Exploring data, reasoning, and algorithmic solutions to ensure Gemini models are safe and work for everyone * Improving Gemini's adversarial robustness, with a focus on high-stakes abuse risks * Designing and maintaining high-quality evaluation protocols to assess model behaviour gaps and headroom related to safety and fairness * Developing and executing experimental plans to address known gaps or construct entirely new capabilities To succeed in this role, you should have a PhD in Computer Science or a related field, significant LLM post-training experience, and a track record of publications at top conferences. Experience in reward modelling and reinforcement learning for LLMs instruction tuning, long-range reinforcement learning, safety, fairness, and alignment is an advantage.
date posted: 2026-03-31T18:27:50.311Z
valid through: 2026-10-01T16:02:53.346Z
direct apply: false
occupational category: Engineering
industry: Technology
skills: PhD in Computer Science or a related field
skills: Significant LLM post-training experience
skills: Post-training/instruction tuning state-of-the-art language models
skills: Exploring data, reasoning, and algorithmic solutions
skills: Improving Gemini's adversarial robustness
skills: Reward modelling and reinforcement learning for LLMs instruction tuning
skills: Long-range reinforcement learning
skills: Safety, fairness, and alignment
hiring organization: Google DeepMind
  type: Organization
  founding date: 2010
  number of employees: QuantitativeValue
    value: 10000
job location: Place
  address: PostalAddress
    address locality: Mountain View
    address country: US
employment type: FULL_TIME