Paola Canale

Key Skills

Software

Appen

Clickworker

CVAT

Other

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Top Task Types

Audio Recording

Classification

Emotion Recognition

Evaluation Rating

Text Summarization

Freelancer Overview

I am an experienced AI Trainer and Language Model Evaluator with a strong background in data labeling, prompt engineering, and multilingual content analysis. I have collaborated with leading AI training platforms such as Telus International AI, DataAnnotation, and Outlier, contributing to high-impact projects across finance, ESG, healthcare, legal, and customer service domains. My work includes evaluating and annotating LLM outputs for truthfulness, toxicity, bias, and localization accuracy, as well as designing prompts and structured workflows for Reinforcement Learning from Human Feedback (RLHF) tasks. What sets me apart is the integration of domain-specific knowledge, particularly in finance and ESG reporting, with AI quality assurance practices. I bring a deep understanding of sustainability frameworks (GRI, SASB, EU Taxonomy), business transformation, and regulatory compliance, which enables precise, context-aware content evaluation. Fluent in Italian, English, and French, I offer multilingual annotation expertise and cross-cultural localization review. With a foundation in MBA-level business administration and certifications in management accounting and ESG, I ensure high standards in both technical accuracy and subject matter relevance.

Labeling Experience

LLM Evaluation & ESG Content Annotation

Data Annotation TechTextClassificationText Generation

Performed expert-level annotation and evaluation of LLM outputs across ESG reporting, healthcare, and finance domains. Labeled and classified text for truthfulness, bias, tone, localization, and regulatory compliance. Supported reinforcement learning from human feedback (RLHF), multilingual evaluation, and prompt engineering for safety-aligned generative AI applications.

Performed expert-level annotation and evaluation of LLM outputs across ESG reporting, healthcare, and finance domains. Labeled and classified text for truthfulness, bias, tone, localization, and regulatory compliance. Supported reinforcement learning from human feedback (RLHF), multilingual evaluation, and prompt engineering for safety-aligned generative AI applications.

2024

Education

Work History