Research Scientist, Gemini Agent Safety Post Training, DeepMind

Google DeepMind; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google DeepMind's 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.

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).

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.

Skills

PhD level research leadership

Three years research program exposure

Publications in AI/ML venues

Education

PhD in Computer Science or related field

Job description

• 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).

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.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google .

• 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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .