# Research Scientist, Interpretability

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA
**Role:** AI Research
**Salary:** $350k – $850k/yr
**Skills:** Python, Mechanistic Interpretability, Neural Networks, LLMs, Transformer Circuits, Experiment Design, Reverse Engineering, Scientific Research, Data Visualization, Infrastructure Development
**Posted:** 2026-02-12

> Conducts mechanistic interpretability research to reverse-engineer language models, developing methods to understand neural network algorithms for AI safety. Requires scientific research background, Python proficiency, and collaborative engineering mindset.

## Job Description

## Responsibilities
- Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights
- Design and run robust experiments, both quickly in toy scenarios and at scale in large models
- Create and analyze new interpretability features and circuits to better understand how models work
- Build infrastructure for running experiments and visualizing results
- Work with colleagues to communicate results internally and publicly

## You may be a good fit if you
- Have a strong track record of scientific research (in any field), and have done *some* work on Interpretability
- Enjoy team science – working collaboratively to make big discoveries
- Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away
- You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results
- You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null

**Familiarity with Python is required.**

**Education requirements:** At least a Bachelor's degree in a related field or equivalent experience.

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