# Member of Technical Staff — ML Research, Interpretability at Causal

- Company: Causal
- What the company does: Backed by Accel.
- Company website: https://www.causal.app/
- Type: Startups (AI role)
- Level: Senior
- Location: San Francisco
- Work setup: On-site
- Posted: 2026-07-20
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/causal/fa803558-a6b4-4721-9909-4295fb3256b0
- Page: https://www.1752.vc/careers/jobs/causal-member-of-technical-staff-ml-research-interpretability/

## About the role

Probe the model's internal representations for physical quantities, structure, and conservation laws Develop methods to explain individual predictions and the model's reasoning about interventions

## What they're looking for

- We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains
- Strong grasp of machine learning fundamentals and the internals of modern neural network architectures
- Experience or strong interest in interpretability, representation analysis, or related research
- Strong engineering skills for building interpretability tooling and running careful experiments
- A rigorous, hypothesis-driven approach to understanding model behavior
- A track record of turning open-ended research questions into concrete findings

Tags: Research