Giuliano Monetti

Key Skills

Software

Mercor

Other

Telus

Top Subject Matter

AI dataset quality and compliance

Language Model (LLM) instruction-following improvement

AI data annotation and labeling for LLMs

Top Data Types

Text

Video

Audio

Image

Document

Top Task Types

Prompt + Response Writing (SFT)

Data Collection

Audio Recording

Freelancer Overview

Quality Reviewer - Mercor. Brings 12+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Mercor, Other, and Telus. Education includes No Degree Awarded, Chapman School of Law (2014) and Master of Arts, Webster University (2013). AI-training focus includes data types such as Text, Video, and Audio and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

AI Trainer - Meridial Marketplace, by Invisible

OtherText

Applied deep expertise in English to stress-test and fine-tune AI models for reliable and human-like language performance. Provided actionable annotations and corrections on diverse datasets to improve AI application efficacy. Focused on language nuances, cultural idioms, and regional variations to enhance model accuracy. • Evaluated AI-generated text for linguistic accuracy and realism. • Annotated datasets to facilitate nuanced model understanding. • Provided detailed corrections for grammar, terminology, and style. • Collaborated in iterative refinement of textual outputs.

Applied deep expertise in English to stress-test and fine-tune AI models for reliable and human-like language performance. Provided actionable annotations and corrections on diverse datasets to improve AI application efficacy. Focused on language nuances, cultural idioms, and regional variations to enhance model accuracy. • Evaluated AI-generated text for linguistic accuracy and realism. • Annotated datasets to facilitate nuanced model understanding. • Provided detailed corrections for grammar, terminology, and style. • Collaborated in iterative refinement of textual outputs.

2026 - Present

AI Data Annotation Specialist - TELUS Digital AI Data Solutions

TelusTextData Collection

Performed data collection, annotation, labeling, and evaluation for AI models in large-scale ML projects. Supported fine-tuning of generative AI and LLMs using human-in-the-loop data tasks. Ensured responsible, ethical, and high-quality training data for advanced models. • Annotated large datasets following strict accuracy guidelines. • Actively participated in data curation and quality assurance. • Maintained consistent labeling throughput to meet project needs. • Protected sensitive data through careful handling and compliance.

Performed data collection, annotation, labeling, and evaluation for AI models in large-scale ML projects. Supported fine-tuning of generative AI and LLMs using human-in-the-loop data tasks. Ensured responsible, ethical, and high-quality training data for advanced models. • Annotated large datasets following strict accuracy guidelines. • Actively participated in data curation and quality assurance. • Maintained consistent labeling throughput to meet project needs. • Protected sensitive data through careful handling and compliance.

2026 - Present

AI Data Specialist - RWS Group

OtherTextData Collection

Performed high-quality data collection, annotation, labeling, and evaluation tasks for large-scale machine learning projects. Supported advancement of generative AI and LLMs by ensuring responsible and ethical training data. Focused on human-in-the-loop data tasks for improved AI fine-tuning. • Ensured data quality through rigorous annotation protocols. • Participated in continual evaluation cycles for labeling accuracy. • Collaborated on large enterprise datasets to support cutting-edge AI models. • Adhered to strict confidentiality and data protection guidelines.

Performed high-quality data collection, annotation, labeling, and evaluation tasks for large-scale machine learning projects. Supported advancement of generative AI and LLMs by ensuring responsible and ethical training data. Focused on human-in-the-loop data tasks for improved AI fine-tuning. • Ensured data quality through rigorous annotation protocols. • Participated in continual evaluation cycles for labeling accuracy. • Collaborated on large enterprise datasets to support cutting-edge AI models. • Adhered to strict confidentiality and data protection guidelines.

2026 - Present

Tier 2 AI Generalist - Mercor

MercorTextPrompt Response Writing SFT

Crafted system prompts with constraints, multi-turn user prompts, and golden responses for LLM chatbot training. Designed realistic conversation flows to improve instruction-following, coherence, and alignment. Iteratively refined and reviewed outputs for compliance with style guides through multiple checks and edits. • Contributed to supervised fine-tuning datasets for enhanced model reliability. • Reviewed and edited golden responses to optimize model output quality. • Honed skills in prompt engineering for optimal LLM performance. • Maintained strict adherence to rubric and style constraints.

Crafted system prompts with constraints, multi-turn user prompts, and golden responses for LLM chatbot training. Designed realistic conversation flows to improve instruction-following, coherence, and alignment. Iteratively refined and reviewed outputs for compliance with style guides through multiple checks and edits. • Contributed to supervised fine-tuning datasets for enhanced model reliability. • Reviewed and edited golden responses to optimize model output quality. • Honed skills in prompt engineering for optimal LLM performance. • Maintained strict adherence to rubric and style constraints.

2026 - Present

Quality Reviewer - Mercor

MercorText

Conducted thorough quality reviews of contractor submissions using detailed rubrics for factual accuracy, coherence, reasoning, and guideline adherence. Provided constructive feedback to contributors to improve performance and ensure client-ready data quality. Ensured high-fidelity data delivery on tight deadlines. • Evaluated data submissions for logical consistency and standards compliance. • Applied rubric-based scoring across a wide variety of content types. • Provided actionable written feedback for contributors. • Maintained client-ready quality through consistent review cycles.

Conducted thorough quality reviews of contractor submissions using detailed rubrics for factual accuracy, coherence, reasoning, and guideline adherence. Provided constructive feedback to contributors to improve performance and ensure client-ready data quality. Ensured high-fidelity data delivery on tight deadlines. • Evaluated data submissions for logical consistency and standards compliance. • Applied rubric-based scoring across a wide variety of content types. • Provided actionable written feedback for contributors. • Maintained client-ready quality through consistent review cycles.

2026 - Present

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Education

Work History