White Circle · AI infrastructure

Research Engineer (Evals)

  • London (Hybrid), +1 more: Paris
  • Full-time
  • Competitive

AI roleMachine LearningTrains models

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Posted
Visa & relocation
  • White Circle offers relocation support for this job

In the job ad:

“Relocation support if you’re moving to Paris, available after your probationary period”
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What you'll do

As written by White Circle · Read the original

About the team

White Circle's fundamental research team works on the science of how AI systems fail in the real world: where agents break, how misalignment actually looks like to the end user, and how it is present in the model internals. We build the evals, benchmarks, environments, and tooling that empirically study high-impact agent reliability concerns — some of which become the guardrails shipped in our products, and some of which become public writeups.

What you’ll do

Own and maintain our internal benchmark suite, covering single/multi-turn content guardrails and agentic safety.

  • Build benchmarks that distinguish specific model capabilities.

  • Work with the product team to build evals covering core functionality of our flagship models.

  • Build benchmarks for new features coming out of the research team.

  • Adapt and extend evals to new verticals and changing product data.

  • Work on research projects that study and quantify realistic agentic and LLM failure modes in the wild.

You’ll fit right in if you

  • Have built an LLM benchmark from scratch that distinguished specific model capabilities (i.e., produced a measurable, defensible capability difference, not just a score).

  • Have built synthetic data for post-training textual or multimodal models.

  • Can reproduce a published benchmark result and identify where the original methodology is fragile or misleading.

  • You write Python that other people can build on. Our whole stack is Python; we want someone who has shipped and maintained production code and who factors messy problems into clean abstractions others can extend.

  • You can write efficient LLM inference setups, including sensible orchestration of parallel calls, retries, rate-limit handling.

  • An AI power-user — fluent with frontier models and coding agents day to day.

Skills

Stack

  • Python
  • Hugging Face Transformers

Working languages

English

Salary & benefits

Compensation & benefits

  • Competitive compensation, including equity

  • Flexible time off

  • Office in central London/Paris with flexible hybrid setup

  • Relocation support if you’re moving to Paris, available after your probationary period

  • Premium private health insurance

  • Mental health support, including coverage for therapy when you need it

  • Lunch and dinner covered when you work from the office

  • Learning and development support for courses, conferences, and opportunities to grow your skills

  • All the hardware, subscriptions, tools, and services you need

  • Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella

Company

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