Interpretability Research Engineer: Build Tools for Safe AI

Anthropic Limited; San Francisco (CA); Hybrid; USD 315,000 - 560,000; Full time

Benefits offered by this job

Equity donation matching

Vacation and parental leave

Flexible working hours

Office space in SF

Job summary

Anthropic is seeking an experienced software engineer to advance the Interpretability team’s infrastructure for training and inference of safety-focused AI models. You will work with researchers and infra teams to optimize performance, instrument activations, and empower rapid experimentation.

Strong candidates will have 5–10+ years building software, expertise in Python and ML stacks (PyTorch/CUDA or JAX), and a passion for interpretability research and its societal impact.

Qualifications

• 5-10+ years of software development experience.
• Proficiency in at least one programming language (Python preferred).
• Interest in interpretability and AI safety.

Responsibilities

• Build and maintain inference and training infrastructure for interpretability research.
• Resolve scaling bottlenecks via profiling and optimization.
• Design tools and platforms enabling rapid researcher experimentation.
• Support production safety audits with reliable tooling.
• Collaborate with researchers and infrastructure teams across the stack.

Skills

Python

Software engineering

5-10 years

Research collaboration

Ambiguity handling

Interpretable AI

Education

Bachelor's degree

Tools

PyTorch

CUDA

JAX

Job description

Anthropic is seeking an experienced software engineer to advance the Interpretability team’s infrastructure for training and inference of safety-focused AI models. You will work with researchers and infra teams to optimize performance, instrument activations, and empower rapid experimentation.

Strong candidates will have 5–10+ years building software, expertise in Python and ML stacks (PyTorch/CUDA or JAX), and a passion for interpretability research and its societal impact.