---
title: Research Scientist, Gemini Agent Safety Post Training
description: Google is hiring for the Research Scientist, Gemini Agent Safety Post Training
  role in Mountain View, CA. See the full description and apply.
type: job
url: https://www.foundrole.com/jobs/research-scientist-gemini-agent-safety-post-training-at-google-01a1ca8c-c15b-7a73-8375-a368e93b43fe
date: 2026-11-15T01:26:44Z
og_description: Join Google as Research Scientist, Gemini Agent Safety Post Training in Mountain
  View, CA. Pays $207K–$300K per year.
og_image: https://www.foundrole.com/og/npenj7.png
breadcrumbs:
  - label: Home
    url: https://www.foundrole.com/
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    url: https://www.foundrole.com/jobs
---

| | |
|---|---|
| **Company** | [Google](https://www.foundrole.com/companies/google?utm_source=ai_markdown) |
| **Location** | Mountain View, CA |
| **Salary** | $207K/yr - $300K/yr |
| **Posted** | Nov 11, 2026 |

## Is this job real?

**Ghost job check:** A- · Low risk. Probably a real opening.

## Visa sponsorship

- **H-1B:** Google sponsors H-1B visas. It filed 9,179 H-1B petitions (FY2026 Q1 – FY2026 Q4).
- **E-Verify:** No E-Verify enrollment on record for Google.

## Pay for similar jobs

Most similar jobs pay $213,000 – $254,000 a year (median $213,000).

## Description

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](https://www.google.com/about/careers/applications/benefits/).

- 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.

### 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).

- 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).
## Skills

- Google Gemini
- Supervised Fine-Tuning (Sft)
- Machine Learning Model Fine-Tuning
- AI Safety
- AI Agents
- Generative AI
- Reinforcement Learning from Human Feedback (Rlhf)
- Instruction Tuning
- Large Language Models (Llm)
- Access Control Lists
- Computer Science
- Reinforcement Learning
- Safety-Critical Systems Engineering
- Model Optimization
- Reward Modeling
- Machine Learning

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