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Member of Technical Staff (Applied AI)

Aptura · London

Publicada em 22/09/2026

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About ApturaWe build the evaluation datasets and RL environments that make AI reliable in domains where mistakes are expensive: finance, healthcare, and legal. Our team designs expert-curated training data, calibrated rubrics, and verifiable task environments for AI labs and startups pushing the frontier of what models can do in regulated industries.We're a small, lean, London based team that moves fast and takes the work seriously. Everyone contributes directly. Initiative is rewarded, and ownership is the default. If you want to shape how frontier AI learns to operate in the real world, we'd like to hear from you.About the RoleAs a Member of Technical Staff on our Applied AI team, you will build the tasks and environments that AI labs use to train and evaluate their agents in finance, healthcare, and legal.Day to day, that looks like: constructing RL environments around spreadsheets, documents, and professional workflows. Writing verification logic and reward functions. Working with domain experts to scope what a correct answer actually looks like in an LBO model or a clinical note. Some days it's engineering, some days it's closer to research. The common thread is that you're producing the ground truth that frontier models get measured against.What You'll DoBuild RL environments across finance, healthcare, and legal domainsAssist in designing tasks with golden answers, calibrated rubrics, and programmatic reward signalsWrite verification logic and reward functions that can distinguish good model outputs from bad onesWork directly with domain experts (investment analysts, physicians, attorneys) to translate complex professional workflows into structured tasksPrototype new approaches to evaluation, verification, and synthetic data generationWho We're Looking ForPractical experience building with LLMs: prompting, evaluation, and agentic harnesses. You've built things that actually run, not just notebooks.High agency and technically sharp. You don't wait for permissi
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