Research Scientist/Engineer (Evaluations)

🏢 Apollo Research · 📍 London & San Francisco · 💼 onsite · ⏰ Full-time

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Position Summary & Responsibilities

Application deadline: We are conducting interviews actively and aim to fill this role as soon as we find someone suitable.

ABOUT THE OPPORTUNITY

We’re looking for Research Scientists/Engineers for our pre-deployment team to work on Training-Run Assessments (TRAs). You will design and build automated pipelines for assessing whether egregious misalignment or scheming are emerging at any point of frontier post-training.

This will involve evaluating and red-teaming of checkpoints at various stages of post-training as well as automated analysis of post-training data.

You will get to work with frontier labs like OpenAI, Anthropic, and Google DeepMind and be among the first to interact with new models before anyone else. Our ideal candidate loves rigorously testing frontier AI models, and enjoys building efficient pipelines for automated analysis.

KEY RESPONSIBILITIES

Run and own pre-deployment engagements: We run a pre-deployment evaluation campaign with a frontier AI lab approximately every two weeks with thousands of runs across hundreds of distinct environments. We explore behaviors learned during training and check for undesirable behaviors like alignment faking, perform targeted follow-up experiments/red-teaming, and report our findings to the frontier AI lab we’re working with.
Develop methodology for training-run assessments: in-between campaigns we improve our methodology, which might mean implementing new evals or building infrastructure for automated red-teaming.

KEY REQUIREMENTS

We don’t require a formal background or industry experience and welcome self-taught candidates.
Software engineering skills: Our entire stack uses Python. We're looking for candidates with strong software engineering experience. Ideally, you have experience shipping and mai

🎯 Candidate Preparation Guide For Apollo Research Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Rigorous assessment of frontier AI safety mechanisms, mechanistic interpretability of neural networks, and academic research rigor.

📋 Preparation Priorities (Key Areas to Clarify):

1. Downplaying existential risks or safety concerns associated with advanced AI deployment
2. Lack of deep technical familiarity with neural network internals or transformer architectures
3. Prioritizing speed of deployment over thorough, scientifically sound safety testing

✨ Recommended Role Alignment Hook:

I advance frontier AI safety by combining rigorous mechanistic interpretability with empirical evaluations of complex neural systems.

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