The Center for AI Safety (CAIS) is a leading research and advocacy organization focused on mitigating societal-scale risks from AI. We address AI’s toughest challenges through technical research, field-building initiatives, and policy engagement, along with our sister organization, Center for AI Safety Action Fund.As a Senior Research Scientist here, you will lead and execute high-impact research that advances the safety and reliability of frontier AI systems, taking ownership of ambitious open problems and seeing them through to publication. We expect senior scientists to set a high bar for research quality and push the team’s thinking forward. You’ll design and run experiments on large language models, build the tooling needed to train and evaluate models at scale, and turn results into publishable research. You’ll collaborate closely with CAIS researchers and external academic and commercial partners, using our compute cluster to run large-scale training and evaluation. The work spans areas like AI honesty, robustness, transparency, and trojan/backdoor behaviors, aimed at reducing real-world risks from advanced AI systems.
Key Responsibilities Include:
Pursue high-value research directions with limited guidance.
Own end-to-end research experiments with full accountability for quality and outcomes.
Train and fine-tune large transformer models across domains.
Build and maintain datasets and benchmarks.
Run distributed training and evaluation at scale.
Lead the writing and publication process on key papers, including driving submissions to top conferences.
Collaborate with researchers and external partners while contributing to shared research direction, responding quickly in research cycles, and elevating the quality of the team’s work.
You might be a good fit if you:
Have a Ph.D. in computer science, machine learning, or a related field with 5+ years of related research experience.
Are familiar with relevant frameworks and libraries (e.g., PyTorch and Hugging Face).
Have extensive experience launching and training distributed ML jobs.
Communicate clearly and promptly with teammates.
Have an extremely strong publication record, with many first-authored work at top venues (NeurIPS, ICML, ICLR, ACL, etc.).
Know someone who could be a great fit for this role? Submit their details through our Referral Form. If we end up hiring your referral, you’ll receive a $1,500 bonus once they’ve been with CAIS for 90 days.The Center for AI Safety is an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, medical condition, marital status, military or veteran status, or any other protected status in accordance with applicable federal, state, and local laws. In alignment with the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.If you require a reasonable accommodation during the application or interview process, please contact contact@safe.ai.We value diversity and encourage individuals from all backgrounds to apply.
