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AI Interpretability Researcher

Aria Watanabe

Full-time · Job · Los_Angeles

About the role

Understanding why a model made a specific prediction isn't just an academic curiosity — it's a regulatory requirement in healthcare, a legal necessity in lending, and a safety imperative in autonomous systems. Our interpretability tools help practitioners understand model behavior at levels ranging from individual predictions to global model properties. You'll advance the state of interpretability methods: developing new techniques for understanding transformer attention patterns, building tools that identify which training examples most influenced a specific prediction, and creating the evaluation framework that measures whether explanations are actually faithful to model behavior rather than post-hoc rationalizations. Interpretability research is at a critical inflection point. Existing methods (SHAP, LIME, attention visualization) work for simple models but break down for large language models and complex architectures. You'll work on the next generation of methods that scale to production-size models while maintaining explanation fidelity.

Responsibilities

  • Develop novel interpretability methods for transformer and large language models
  • Build tools identifying training example influence on specific predictions
  • Create evaluation frameworks measuring explanation faithfulness to model behavior
  • Scale interpretability methods to production-size models without prohibitive cost
  • Publish research and contribute to the interpretability research community

Requirements

  • PhD or equivalent experience in ML interpretability or explainability research
  • Strong PyTorch skills for custom model analysis tools
  • Published work in interpretability, explainability, or model analysis
  • Deep understanding of transformer architectures and attention mechanisms
  • Ability to bridge theoretical research with practical engineering needs

Benefits

  • Fully remote — US West Coast hours
  • $200k+ base with equity
  • Dedicated research GPU budget
  • Conference travel and publication support

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Categories

AI & Machine Learning Engineers

Skills

python pytorch statistics hugging face docker

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

AI & Machine Learning Engineers

Skills

python pytorch statistics hugging face docker

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