White Circle
Research Scientist (AI Behaviours)

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TLDR
We're looking for a research scientist to study how LLM agents fail in the wild, who can elicit deception, misalignment, and unsafe behaviour in concrete experiments, and build out the understanding of how agents break or misbehave in realistic and user-related scenarios.
About Us
White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale.
- We’ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
- We process over 100M+ API calls every month
- We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model
We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need.
About The Team
White Circle's fundamental research team works on the science of how AI systems fail: where agents break, why misalignment and unsafe behaviours emerge, and how to catch them before they reach the real world. We build the evals, benchmarks, environments, and tooling that empirically study the most pressing AI safety concerns — some of which become the guardrails shipped in our products, and some of which become public writeups.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You will:
- Own research projects end to end — from an unclear concern ("how do we even define sloppy research outputs?") to a falsifiable experiment, clean baselines, and a result you can defend.
- Develop automated audit agents that discover and characterise suspect model behaviour at scale.
- Study how misalignment and bias actually show up when real users interact with agents, and turn what you find into evals our products can ship.
- Pressure-test frontier agents in realistic, high-stakes scenarios to find where they break before our customers do.
- Run white-box and block-box investigations to understand how AI models fail.
- Publish what you learn as public blog posts and conference papers, and feed the rest back into our internal guardrails.
You’ll fit right in if you:
- A track record of empirical research in agent behaviour, model evaluation, alignment, or a closely adjacent area.
- Strong ML engineering. You can independently build a research MVP involving fine-tuning, agent inference, and evals, without waiting on a platform team.
- Evidenced skills in experimental design under real conditions: isolating agent failure modes, calibrating judges and baselines, and distinguishing genuine signal from artifact.
- You can take a vague behavioural question and define the experiment that answers it, when there's no playbook — then run it fast and iterate.
- An AI power-user — fluent with frontier models and coding agents in your daily work.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
A big plus:
- Published research at A* venues (NeurIPS / ICML / ICLR / ACL and similar).
- Interpretability depth — familiarity with modern interp tooling and concepts (NLAs, SAEs, persona vectors, etc.) and the ability to run whitebox investigations on our internal and open-source models.
- An MSc or PhD in machine learning, computer science, cognitive science, computational neuroscience, physics, or a related quantitative field.
- AI safety fellowship (MATS, ASTRA, Anthropic Fellows, etc.), or a comparable self-directed research record.
Why White Circle
- Paid time off in line with your local regulations, no matter where you work from.
- Work from Paris (hybrid) with a relocation package available, or work from London (note: we are currently unable to provide relocation support or medical insurance for London-based roles).
- Comprehensive medical insurance for our France-based team.
- All the hardware, tools, and services you need.
- Covered subscriptions for AI agents and IDEs.
- Team off-sites twice a year: we’ve recently been to the Alps and to Saint-Tropez.
How We Hire
- Introductory call with HR (25 min)
- Take-home test task
- Technical interview with Head of Fundamental Research (60 min)
- Final conversation with our CEO (45 min)
Please submit your application in English.
Compensation Range: $150K - $250K
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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