About Nebuly
Nebuly is a fast-growing, VC-backed startup building the platform that proves the ROI of enterprise AI.
Every enterprise function — sales, customer support, HR, finance — is deploying AI agents at scale, and budgets are following fast. But most companies can't answer a basic question: is this spend actually working? Every enterprise deploying AI agents is asking the same question: is this actually delivering value? Today, almost none of them can answer it. The signal that could answer it is right there — millions of conversations happening every day between employees, customers, and these agents — but it's unstructured, high-volume, and invisible without the right infrastructure. So the ROI question stays unanswered, not because the answer doesn't exist, but because no one can see it. Nebuly makes that signal visible. It sits on top of any enterprise AI deployment, turns those conversations into a clear answer — is this working, and where — and connects the dots back to ROI. Think of it as the accountability layer for enterprise AI: connect once, see the impact, prove the value — with no data ever leaving your environment.
Every new data category has created a new software category. CRM turned customer interactions into pipeline accountability. Product analytics turned user behavior into growth accountability. Nebuly is building that same layer for AI — turning millions of invisible conversations into a clear answer on value.
Our customers include Oura, CNH Industrial, Vodafone, and Moncler. Demand is accelerating fast, and we're building the team to match.
Team Overview
The Data Labeling team at Nebuly is responsible for annotating and validating the conversation data used to train, evaluate and improve our purpose-built models. These models classify enterprise AI conversations and extract the signals behind them, such as topics, intents, task outcomes and user needs. By ensuring high-quality, accurate and consistent annotations, the team provides a critical foundation for the reliability of the insights our customers act on, and for the continuous improvement of our ML solutions.
Key Responsibilities
Data Annotation: annotate and categorize conversations between users and AI agents according to predefined guidelines, customer-specific taxonomies, project requirements and quality standards.
Quality Assurance: ensure the accuracy, consistency and reliability of labeled datasets through quality checks, review of disagreements between annotators and validation processes. Small differences in labels can change the insights customers see, so consistency matters.
Cross-functional collaboration: Work closely with AI Engineers to ensure labeled data meets model training requirements, and help refine guidelines and category definitions as models, customers and use cases evolve.
Requirements
Languages: proficiency in English, spoken and written, with the ability to interpret conversations accurately.
Mindset: proactive, attentive and highly engaged, with strong attention to detail and the ability to stay focused and consistent on repetitive tasks.
Location: based in Turin, Italy.
What We Offer
Duration: 4-month internship, with the possibility of extension up to 6 months in total.
Compensation: €1,000 net per month.