Application Guide
How to Apply for Research Engineer, Interpretability
at Anthropic
🏢 About Anthropic
Anthropic is a frontier AI research company focused specifically on AI alignment, safety, and interpretability, distinguishing itself by prioritizing responsible AI development over pure commercial objectives. The company's mission-driven approach and focus on high-impact research make it appealing to those wanting to work on cutting-edge AI safety problems with societal importance.
About This Role
This Research Engineer role focuses on implementing and scaling interpretability experiments for large language models, building research infrastructure, and developing tools to make interpretability findings actionable for improving model safety. The position bridges research and engineering by enabling rapid experimentation at scale while ensuring reliability and efficiency in safety-critical research workflows.
💡 A Day in the Life
A typical day might involve implementing a new interpretability experiment on a toy model to test a hypothesis, then scaling it to run on Anthropic's large models while optimizing for computational efficiency. You'd likely collaborate with researchers to understand their needs, build abstractions to make experiments more reproducible, and develop tools that help other teams apply interpretability insights to improve model safety.
🚀 Application Tools
🎯 Who Anthropic Is Looking For
- A software engineer with 5-10+ years experience who can build robust systems for large-scale AI experiments while being productive in Python
- Someone with hands-on experience contributing to empirical AI research projects, particularly in interpretability, alignment, or related safety areas
- A pragmatic problem-solver who can prioritize high-impact work, operate with ambiguity, and question research assumptions to improve experimental design
- An engineer who enjoys building tools and abstractions to accelerate research cycles while maintaining production-quality standards
📝 Tips for Applying to Anthropic
Highlight specific examples where you've built research infrastructure or tools that accelerated experimentation cycles in AI/ML projects
Demonstrate your ability to work at both toy-scale for rapid prototyping and production-scale for large models, with concrete metrics on efficiency improvements
Showcase experience with interpretability techniques (like activation patching, circuit analysis, or feature visualization) even if in smaller projects
Emphasize instances where you've operated with ambiguity in research settings and made judgment calls about what experiments to prioritize
Include links to relevant open-source contributions, research code repositories, or technical blog posts about interpretability or AI safety engineering
✉️ What to Emphasize in Your Cover Letter
['Your experience building and optimizing research workflows for AI experiments, particularly at scale', 'Specific contributions to interpretability or alignment research projects, highlighting your engineering role', "How you've balanced rapid experimentation with building reliable, maintainable systems", "Why Anthropic's mission-focused approach to AI safety resonates with your career goals"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Anthropic's research papers on interpretability (like 'Towards Monosemanticity' or 'Scaling Monosemanticity') and their technical blog
- → The company's Constitutional AI framework and how interpretability research supports it
- → Anthropic's stance on responsible scaling policies and AI safety standards
- → Interviews with Anthropic researchers about their interpretability work and engineering challenges
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on general ML engineering without demonstrating specific interpretability or AI safety experience
- Presenting yourself as purely a researcher without strong engineering credentials for building scalable systems
- Showing limited understanding of Anthropic's specific mission and how it differs from other AI labs
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!