Apollo Research · AI infrastructure
Research Scientist (Control)
- London (On‑site), +1 more: San Francisco
- Full-time
- Competitive
AI roleMachine LearningTrains models
Still open on Apollo Research's site · checked 5 hours ago
- Experience
- 2+ years
- Posted
- Visa & relocation
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Research Scientist (Control)
Apollo Research
What you'll do
As written by Apollo Research · Read the original
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 Research Scientist (Control), 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
REPRESENTATIVE PROJECTS
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Hierarchical monitoring for coding agent security: Design a multi-layer monitoring system for detecting security vulnerabilities introduced by coding agents. Start by cataloging common security failure modes (e.g., hardcoded credentials, SQL injection vulnerabilities, insecure API calls). Build specialized monitors for each category, then create a hierarchical system where fast, efficient first-pass monitors flag potentially problematic code for deeper investigation by more sophisticated monitors.
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Design a backtesting strategy for Watcher: Validate the system on synthetic test cases and real agent outputs, iterating to optimize the tradeoff between detection rates and false positives while maintaining low latency for most monitoring decisions.
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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 with high-quality ground truth labels. Test different fine-tuning techniques and measure generalization to our held-out data. Compare against prompted baselines on accuracy, cost and latency. The goal is to fine-tune models to lift the pareto frontier of monitors.
ABOUT THE TEAM
The product team consists of research scientists: Victor Gillioz, Monika Jotautaitė, Dmitrii Volkov; product engineers: Jeremy Neiman, Zak Walters, Zen van Riel, Srdjan Miletic and Gustavo Bicalho; and our GTM lead: Kyle Dai. Marius Hobbhahn (CEO) advises the team. Furthermore you will interact with our other SWEs and researchers, since we intend to be "our own customer" by using our products internally for our research work. You can find our full team here.
Requirements
Must-haves
2+ years of experience conducting empirical research with large language models or AI systems
Strong experience with AI coding agents. For example, having extensively used and compared frontier coding agents, or having designed / developed 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 e.g. prompting, scaffolding, agent design, fine-tuning, or RL
Strong Python programming skills
Demonstrated ability to work independently on open-ended research problems
Skills
Stack
- Python
- SQL
Working languages
English
Salary & benefits
BENEFITS
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This role offers market competitive salary, equity, and competitive benefits.
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Salary: San Francisco: $204,000 – $385,000; London: £136,000 – £258,000. We will be looking to meaningfully raise salaries soon.
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Flexible work hours and schedule
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Unlimited vacation
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Unlimited sick leave
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Up to 6 months of paid parental leave
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Comprehensive health, dental and vision insurance
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Retirement savings with competitive employer matching (e.g. 401(k) for US employees)
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Lunch, dinner, and snacks are provided for all employees on workdays
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Paid work trips, including staff retreats, business trips, and relevant conferences
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A yearly $1,000 (USD) professional development budget
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Relocation support and visa fees (if applicable)
Company
Last checked . The details above were extracted automatically; the employer's original posting is the authority.