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Research Scientist, Gemini Agent Safety Post Training, DeepMind

DeepMind

Mountain View, CAJob$207–300K/yrPosted 2 days agoStill listed today

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At a glance

Compensation
$207–300K/yr
Location
Mountain View, CA
Work Authorization
Not specified

Olive focuses on jobs in the United States, including remote roles you can work from there.

Job overview

The Research Scientist will develop algorithmic solutions for Gemini safety and bring large language model post-training expertise to ensure aligned, production-ready outputs. The role focuses on identifying safety gaps, applying modeling and alignment techniques, advancing supervised fine-tuning and reinforcement learning, and partnering with post-training, evaluation, and product teams. The team works to improve protections across Gemini and generative AI models.

Skills & qualifications

RequiredNice to have

Skills

Computer Science, nice to haveMachine Learning, nice to haveReinforcement Learning, nice to haveResearch Agenda Execution, requiredAcademic Project Leadership, requiredAI Safety, nice to haveModel Alignment, nice to haveAI Agent Development, nice to haveSafety-Critical Systems, nice to haveMachine Learning Infrastructure, nice to haveReward Modeling, nice to haveLLM Instruction Tuning, nice to haveLong-Range Reinforcement Learning, nice to haveEngineering, nice to haveExperimental Work, nice to have

Qualifications

PhD in Computer Science or Related Field or Equivalent Practical Experience, required3 Years Research Agenda or Academic Project Experience, requiredPeer-Reviewed Publication Submission or Public Preprint, required

Full job description

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Minimum qualifications:

  • PhD in Computer Science, a related field, or equivalent practical experience.
  • 3 years of experience initiating, scoping, and executing research agendas or leading academic projects.
  • One or more peer-reviewed scientific publication submissions (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, CoRL) or public preprint repositories (arXiv).

Preferred qualifications:

  • Experience in AI safety and model alignment.
  • Experience developing AI agents, safety-critical systems, or Machine Learning Infrastructure.
  • Expertise in reward modeling, Reinforcement Learning (RL) for LLMs, instruction tuning, and long-range RL.
  • Ability to drive research concepts to product realization with a strong track record of engineering abilities and experimental work.
  • Track record of publications at AI/ML venues (e.g., NeurIPS, ICLR, ICML, EMNLP, AAAI, UAI).

About the job The Gemini Safety team is accountable for the standards of GDM’s flagship releases. In this role, you will develop algorithmic solutions to advance user-facing architectures. The workstyle is changing, supported by a strong internal culture of mutual dedication and cooperation. You will bring a Large Language Model (LLM) post-training expertise to ensure outputs are aligned and production-ready. You will be a builder and shipper who takes end-to-end ownership. 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. We are pushing the boundaries across multiple domains. Our global teams offer diverse 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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities

  • Design, implement, and maintain high-quality protocols to identify safety gaps in model behavior across all Gemini and GenAI models, and feed these insights back into the post-training process to continuously improve both in-model and out-of-model protection.
  • Explore, adapt, and apply innovative modeling and alignment techniques to solve real-world safety and alignment issues under tight launch timelines.
  • Drive innovation in model optimization, advancing the application of Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) techniques at massive scale.
  • Partner closely with post-training, evaluation, and product teams to align incentives, close safety gaps, and influence safety decisions without direct authority.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire. If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form. Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

How this job compares

Set against the 2,131 open Research Scientist jobs on Olive Jobs, counted November 14, 2026.

Pay
  • This posting$207–300K/yr
  • California median$174–265K/yr471 salary ranges
  • US median$135–222K/yr1,534 salary ranges

This range's midpoint, $254K, is 17% above the California median midpoint ($216K) — in the middle half of Research Scientist salary ranges in California.

Openings
Olive Jobs lists 659 open Research Scientist jobs in California and 2,131 across the US. 3% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 3 years of experience; Research Scientist postings that state a minimum ask for 3 years at the median (1,196 postings).
Education
1,051 of the 2,131 open Research Scientist jobs (49%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 14, 2026. Figures based on too few postings are left out.

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