仕事内容
<div class="content-intro"><h2><strong>About Anthropic</strong></h2>
<p>Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><h2>About the role:</h2>
<p>When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?"</p>
<p>The Interpretability team at Anthropic works to understand what's actually happening inside trained models - and applies our best techniques to keep frontier AI safe as it rapidly improves.</p>
<p>Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs.</p>
<p>More resources to learn about our work: </p>
<ul>
<li>
<p><a href="https://transformer-circuits.pub/" target="_blank">Our Research blog</a> - covering advances including <a href="https://transformer-circuits.pub/2024/scaling-monosemanticity/" target="_blank">Monosemantic Features</a> and <a href="https://transformer-circuits.pub/2025/attribution-graphs/methods.html" target="_blank">Circuits</a></p>
</li>
<li>
<p><a href="https://www.youtube.com/watch?v=TxhhMTOTMDg" target="_blank">An Intro to Interpretability</a> from our research lead, <a href="https://colah.github.io/about.html" target="_blank">Chris Olah</a></p>
</li>
<li>
<p><a href="https://www.darioamodei.com/post/the-urgency-of-interpretability" target="_blank">The Urgency of Interpretability</a> from CEO Dario Amodei</p>
</li>
<li>
<p><a href="https://www.anthropic.com/research/engineering-challenges-interpretability" target="_blank">Engineering Challenges Scaling Interpretability</a> - directly relevant to this role</p>
</li>
<li>
<p><a href="https://youtu.be/aAPpQC-3EyE?si=C2jqlXb15OIJSkMk&t=487" target
求めるスキル
Python
Kubernetes
AWS
GCP
Rust