D

dmodel

AI interpretability research lab and partnerships

Member of Technical Staff

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Strong proficiency in Python and machine learning frameworks such as PyTorch or JAX.
  • Familiarity with alignment and/or interpretability literature.
  • Ability to generate research ideas in the field and implement ideas from others.

Responsibilities

  • Build reinforcement learning environments and evaluations to test how AI agents approach alignment problems.
  • Develop graders robust to specification gaming.
  • Find novel interpretability and alignment techniques.
  • Present findings in team research meetings and contribute to papers in machine learning.
  • Run experiments and identify patterns in model behavior and failure modes.
  • Investigate AI interpretability techniques within reinforcement learning environments.

Desired Qualifications

  • Published or presented research in AI safety, especially mechanistic interpretability.
  • Graduate degree in physics or mathematics, or equivalent research experience.
  • Academic research experience.
  • Experience post-training language models.

About the Company

dmodel

AI interpretability research lab and partnerships

d model (dmodel.ai) is an AI research lab that partners with frontier labs to advance interpretability and alignment research. It develops agents and tools to study how to make AI models safer and easier to steer, focusing on independent interpretability research rather than exploiting rewards. The company shares RL environments for open-ended interpretability tasks and publishes research on concept-editing algorithms discovered by large language model agents. It also seeks researchers to work on interpretability projects that teach agents real research skills rather than reward hacks. The business model centers on partnership-driven AI interpretability R&D with frontier lab collaborators. Overall goal: improve AI safety and controllability by building practical interpretability methods, environments, and agents through collaborative research.

Company size
11-50
Company stage
Seed
Total funding
$130K
Headquarters
San Francisco, CA
Founded
2024

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