- Location
- Mountain View, CA, United States · Onsite
- Compensation
- $207,000 - $300,000 USD annually
- Employment
- Not stated
- Experience level
- MID (3–5 years exp)
- Specialization
- Research Scientist, Scientist, Google
- Source
Role Overview
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.
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.
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.
Requirements & Qualifications
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).
Application Instructions
Apply directly on Google Careers at Research Scientist, Gemini Agent Safety Post Training, DeepMind.
Direct application sign-in: Submit Application