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Apollo Research

Audits AI models for deceptive alignment

Lead Research Scientist/Engineer - Embedded Evaluations

AI ResearchConfirmed live in the last 24 hours
Full-time$245k - $590k

About the Job

Requirements

  • Have a strong track record of producing or leading technically rigorous research relevant to understanding and reducing risks from advanced artificial intelligence, such as alignment, interpretability, model evaluations, control, adversarial machine learning, or post-training.
  • Understand modern model training well enough to interrogate a lab’s methods and learn unfamiliar pipelines quickly.
  • Have led ambitious technical projects end-to-end under hard deadlines and managed or closely supervised strong individual contributors.
  • Be able to set research priorities, delegate meaningful ownership, review technical work, and keep a team focused on the questions that matter most.
  • Be able to extract signal from large, messy datasets, use quantitative analysis and determine when qualitative assessment is more appropriate, and identify anomalies and unexpected model behaviors.
  • Have experience writing about qualitative and quantitative findings for different stakeholders and communicating unorganized technical information effectively to lab safety teams, lab leadership, governments, or the public.
  • Have a strong conceptual understanding of scheming concepts such as metagaming, evaluation awareness, deception, and reward-seeking, and be familiar with classic and modern research in the area.
  • Be capable of using AI to accelerate technical or other work, have experience using different models and selecting which to use for particular tasks, know when not to use AI, and experiment with new AI workflows.
  • Be able to represent Apollo independently in sustained, high-stakes technical collaborations and tactfully resolve disagreements with partners or stand firm in negotiations.
  • Be committed to the organization’s mission of reducing advanced AI loss-of-control risks.

Responsibilities

  • On the on-site embedded evaluator team, spend weeks or months embedded at a frontier AI lab; conduct interviews, review the lab’s evidence, gather new evidence, and write a report.
  • Execute the on-site evaluator playbook quickly and adapt to unforeseen circumstances.
  • Initially work on the applied research team to gain context on embedded evaluations before potentially being sent into an embedded campaign.
  • Prepare on-site evaluators before they are embedded and support them while they are embedded.
  • Determine what evidence would support a safety case and write playbooks to help on-site evaluators gather evidence quickly.
  • Develop tools for embedded evaluators ahead of time and urgently on demand.
  • Bridge fundamental research and on-site evaluators, including converting research methodologies into turnkey code and procedures.

Desired Qualifications

  • Deep experience with frontier reinforcement learning or post-training.
  • Strong software engineering skills; the organization’s technology stack uses Python.
  • Previous experience in professional services such as auditing or consulting, including lessons from on-site client work that can generalize to working with frontier AI labs.

About the Company

Apollo Research

Audits AI models for deceptive alignment

Apollo Research is an AI safety organization that audits high-risk failure modes in large AI models, with a focus on deceptive alignment where models pretend to be aligned while pursuing their own objectives. It conducts fundamental research in interpretability and behavioral model evaluations, then applies these insights to audit real-world models. By combining examination of model internals with behavioral assessments, Apollo Research aims to provide stronger safety assurances than relying on behavioral evaluations alone. Its goal is to minimize catastrophic risks associated with advanced AI systems and ensure more reliable, safe behavior in deployed models.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2023

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