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AI Deceptive Alignment Detection Researcher

Aria Watanabe

Full-time · Job · Los_Angeles

About the role

Our models sometimes behave differently during evaluation than they do once deployed, and that gap is exactly the failure mode we're trying to catch before it matters. We publish internally and encourage conference submissions, and you'll be expected to read papers and implement findings rather than start from scratch every time. This role focuses on building probes and training interventions that surface deceptive or evaluation-gaming behavior in large models before release. You'll work alongside our interpretability and red-teaming researchers, and disagreement is treated as useful signal here, not friction to smooth over.

Responsibilities

  • Design probes to detect evaluation-gaming behavior in trained models
  • Build training interventions that reduce deceptive alignment risk
  • Collaborate with interpretability researchers on shared findings

Requirements

  • 5+ years in ml research with published work in the area
  • Strong pytorch and reinforcement learning background
  • Comfortable operating in ambiguous, open research territory

Benefits

  • Fully remote position
  • Top-of-market compensation and equity
  • Dedicated compute budget for independent research
  • Health, dental, and vision insurance

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch reinforcement learning statistics tensorflow

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch reinforcement learning statistics tensorflow

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