How to apply for Research Scientist, Member of Technical Staff, AI Digest

About Sage

Sage is a unique nonprofit dedicated to forecasting AI progress and its risks, offering a mission-driven environment where your research directly contributes to understanding and mitigating AI dangers. Working at Sage means being at the forefront of AI safety, with a focus on empirical, data-driven insights rather than theoretical speculation.

About the role

As a Research Scientist on the AI Digest team, you will lead research initiatives using AI Village data to uncover critical insights about frontier AI agents' capabilities and behaviors. This role is impactful because your findings will inform the broader AI safety community and potentially influence policy and development practices.

A typical day

A typical day might start with reviewing data from AI Village, then designing and running experiments to test a hypothesis about agent behavior. You'd spend time coding, analyzing results, and documenting findings, with opportunities to collaborate with the team remotely and share insights. The role offers flexibility and autonomy, but also requires rigorous documentation and communication of your research.

Who Sage is looking for

• Strong background in AI/ML research with demonstrated experience in designing and executing experiments on AI agents.
• Proven ability to work independently, with a bias for action and rapid prototyping in research environments.
• Excellent data analysis skills, including statistical methods and proficiency with tools like Python, PyTorch, and data visualization libraries.
• Familiarity with AI safety, interpretability, or forecasting is a plus, along with a passion for understanding emergent AI behaviors.

Tips for this application

• Tailor your resume to highlight any experience with AI agent evaluation, sandbox environments, or large-scale data analysis, as these are core to the role.
• In your application, include a brief description of a research project where you independently designed and executed an experiment, emphasizing the impact of your findings.
• Demonstrate your familiarity with AI Village or similar simulation platforms by mentioning any relevant work or side projects in your cover letter.
• Showcase your ability to communicate complex findings clearly, as the role involves surfacing insights to a broader audience.
• Before applying, explore Sage's website and any public publications to understand their current research focus, and reference this in your application to show genuine interest.

What to cover in your cover letter

['Highlight your experience with AI agents and your ability to design experiments that test hypotheses about their behavior.', 'Emphasize your independence and bias towards action, with examples of self-driven research initiatives.', "Connect your skills to Sage's mission of forecasting AI risks, explaining how your research can contribute to their goals.", 'Mention any familiarity with AI safety or forecasting, and how your background aligns with the interdisciplinary nature of the team.']

Research before applying

• Read Sage's publications and blog posts to understand their current research on AI forecasting and risk assessment.
• Familiarize yourself with AI Village, including its data structure, available environments, and any public documentation or tutorials.
• Look into recent papers on AI agent evaluation, such as those from ARC, OpenAI, or DeepMind, to understand the state of the art.
• Research the broader AI safety landscape, including organizations like MIRI, FLI, and others, to contextualize Sage's role.

Likely interview topics

Based on the job description, expect questions about:

• How would you design an experiment to test a specific capability of a frontier AI agent using AI Village?
• What methods do you use to analyze large-scale data from AI simulations, and how do you ensure statistical rigor?
• Describe a time when you had to rapidly prototype a research environment or tool—what was your approach?
• How do you prioritize research questions when working independently on multiple potential avenues?
• What do you think are the most critical risks in AI development, and how can empirical research address them?

Common mistakes to avoid

• Avoid applying with a generic resume that doesn't highlight relevant experience with AI agents or simulation environments.
• Don't overlook the importance of communication skills—ensure your application and interview responses clearly articulate your research findings.
• Steer clear of focusing only on theoretical aspects; emphasize hands-on, empirical research experience.