Applied Control Researcher in London

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

THE OPPORTUNITY

Join our new AGI safety product team and help transform AI control research into practical tools that directly reduce risks from AI. As an applied control researcher, you’ll work closely with Marius (CEO & currently leads the monitoring efforts), other control researchers and product engineers.

We are currently building Watcher, a monitoring tool for coding agents. Our monitoring research agenda attempts to translate compute into safety at scale. You will join a small team and will have significant ability to shape the team & tech, and have the ability to earn responsibility quickly.

You will like this opportunity if you're passionate about using empirical research to make AI systems safer in practice. You enjoy the challenge of translating theoretical AI risks into concrete detection mechanisms. You thrive on rapid iteration and learning from data. You want your research to directly impact real-world AI safety.

KEY RESPONSIBILITIES

TLDR: you will design & implement control protocols and test them on real-world production systems at scale.

• Research & Development

• Systematically collect and catalog coding agent failure modes from real-world instances, our internal deployments, public examples, research literature, and theoretical predictions.
• Design and conduct experiments to test monitor effectiveness across different failure modes and agent behaviors.
• Build and maintain evaluation frameworks to measure progress on monitoring capabilities.
• Build and maintain high-quality datasets to train and test monitors on.
• Iterate on monitoring approaches based on empirical results, balancing detection accuracy with computational efficiency.
• Stay current with research on AI safety, agent failures, and detection methodologies.
• Stay current with research into coding security and safety vulnerabilities.

• Develop & maintain a comprehensive library of monitoring prompts tailored to specific failure modes.
• Experiment with different reasoning strategies and output formats to improve monitor reliability.
• Design and test hierarchical monitoring architectures and ensemble approaches.
• Optimize log pre-processing pipelines to extract relevant signals while minimizing latency and computational costs.
• Implement and evaluate different scaffolding approaches for monitors.

• Fine-tune open-source models to create efficient monitors for high-volume production environments.
• Design and build agentic monitoring systems that autonomously investigate logs to identify both known and novel failure modes.
• Build automated red-teaming pipelines that attack monitors at scale.
• Design iterative adversarial games where a red-team and blue team continuously attack and defend respectively.

JOB REQUIREMENTS

• 2+ years of experience conducting empirical research with large language models or AI systems.
• Strong experience with AI coding agents.
• Experience with LLM-as-a-judge setups or AI monitoring more broadly.
• Experience designing and running experiments, analyzing results, and iterating based on empirical findings.
• Strong Python programming skills.
• Demonstrated ability to work independently on open-ended research problems.

Bonus:

• Familiarity with AI safety concepts, particularly agent-related risks.
• Familiarity with computer security.
• Experience fine-tuning language models or working with smaller open-source models.
• Previous work building developer tools or monitoring systems.
• Publications or contributions to AI safety or ML research.
• Experience with production log systems or production log analysis.

We want to emphasize that people who feel they don't fulfill all of these characteristics but think they would be a good fit for the position nonetheless are strongly encouraged to apply.

WHAT YOU'LL ACCOMPLISH IN YOUR FIRST YEAR

• Build a comprehensive failure mode database: Systematically collect and categorize 100+ distinct AI agent failure modes across safety and security dimensions.
• Develop and validate monitoring approaches: Create and empirically test monitoring prompts and strategies for key failure categories.
• Optimize the monitoring pipeline: Improve log preprocessing and monitor scaffolding to achieve measurable improvements in detection accuracy, false positive rates, and computational efficiency.
• Advance monitoring capabilities: Work on advanced approaches such as fine-tuned monitors or agentic investigation systems.

REPRESENTATIVE PROJECTS

• Hierarchical monitoring for coding agent security: Design a multi-layer monitoring system for detecting security vulnerabilities introduced by coding agents.
• Design a backtesting strategy for Watcher: Validate the system on synthetic test cases and real agent outputs.
• Fine-tune an open-source model to be a great monitor: Take an open-source model and fine-tune it on our large dataset of coding agent failures.

BENEFITS

• This role offers market competitive salary, equity, and competitive benefits.
• Salary: 100k - 200 GBP (~135k - 270k USD).
• Flexible work hours and schedule.
• Unlimited vacation.
• Unlimited sick leave.
• Up to 6 months of paid parental leave.
• Comprehensive health, dental and vision insurance.
• Retirement savings with competitive employer matching.
• Lunch, dinner, and snacks are provided for all employees on workdays.
• Paid work trips, including staff retreats, business trips, and relevant conferences.
• A yearly $1,000 (USD) professional development budget.

LOGISTICS

• Time Allocation: Full-time.
• Location: This is an in-person role working out of our London or San Francisco office.
• Visa sponsorship: We sponsor visas in both the UK and US.

ABOUT THE TEAM

The Product team is a new team. You will work closely with Marius Hobbhahn (CEO), Victor Gillioz (Research Scientist), Monika Jotautaitė (Research Scientist), and our product engineers.

ABOUT APOLLO RESEARCH

The rapid rise in AI capabilities offer tremendous opportunities, but also present significant risks. At Apollo Research, we’re primarily concerned with risks from Loss of Control. We work on the detection of scheming, the science of scheming, and scheming mitigations.

EQUALITY STATEMENT

Apollo Research is an Equal Opportunity Employer. We value diversity and are committed to providing equal opportunities to all.

HOW TO APPLY

Please complete the application form with your CV. The provision of a cover letter is neither required nor encouraged.

About the interview process: Our multi-stage process includes a screening interview, a take-home test, technical interviews, and a final interview with Marius (CEO).

Your Privacy and Fairness in Our Recruitment Process: We are committed to protecting your data, ensuring fairness, and adhering to workplace fairness principles in our recruitment process.