Guillermo R.

Key Skills

Software

Other

Don't disclose

Top Subject Matter

LLM training-data creation and evaluation

LLM supervised fine-tuning (SFT) dataset creation and annotation

LLM RLHF preference data preparation

Top Data Types

Text

Document

Top Task Types

Prompt + Response Writing (SFT)

RLHF

Freelancer Overview

Independent Software Developer — AI training data and evaluation (datasets, SFT examples, rubric-based annotation and sc. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Don't disclose. Education includes AWS Certified Solutions Architect - Associate, Amazon Web Services (AWS) (2023) and AWS Certified Big Data - Specialty, Amazon Web Services (AWS) (2019). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation, Rating, and Prompt + Res

Labeling Experience

Independent Software Developer - Independent Software Developer

Text

Independent software developer delivering AI training-data evaluation and related backend tooling under client specifications. Responsibilities included building and maintaining data-processing pipelines, testing code and model outputs for correctness and edge cases, and applying rubric-based evaluation criteria with strict guideline adherence. The role required strong proficiency in Python and JavaScript, backend and distributed-systems experience, and careful security and correctness vetting across multi-language codebases. • Created and curated datasets with SFT-style examples and high-precision annotation aligned to evolving guidelines • Built backend services and data-processing pipelines, performing debugging, code review, and correctness/security checks • Tested and evaluated Python and JavaScript code and model outputs using scoring rubrics and clear failure documentation • Developed LLM tooling including prompt/context engineering, agent workflows, and inference tooling in Python

2021 - Present

Independent Software Developer — RLHF preference ranking and related labeling

Don't discloseTextRLHF

Supported RLHF-style preference ranking as part of the training data and evaluation workflow. Applied rubric-based criteria aligned with model quality and reasoning expectations. Maintained high-precision vetting to ensure preferences and labels were consistent with detailed guidelines. • RLHF preference ranking support • Rubric-driven quality criteria for preferences • Consistency checks against detailed guidelines • High-precision technical vetting of labeled outputs

2021 - Present

Independent Software Developer — AI dataset creation and SFT example annotation

Don't discloseTextPrompt + Response Writing (SFT)

Created and curated datasets for AI model training, including structured data generation and SFT-style example creation. Produced high-precision annotations following detailed guidelines that evolved over time. Ensured strong guideline adherence while preparing training-ready examples for LLM tooling. • Structured data generation for model training • SFT-style example creation • High-precision guideline-based annotation • Ongoing dataset curation against evolving labeling guidelines

2021 - Present

Independent Software Developer — AI training data and evaluation (datasets, SFT examples, rubric-based annotation and scoring)

Other

Provided rubric-based scoring for model outputs and reasoning quality against detailed, evolving guidelines. Tested code and model outputs to verify correctness, document failures, and handle edge cases. Applied systematic compliance and evaluation criteria to ensure high-precision technical vetting of results. • Rubric-based annotation and evaluation of model outputs • Code and model testing for correctness and reasoning quality • Edge-case evaluation and failure documentation • Systematic adherence to complex evaluation/compliance criteria

2021 - Present

Education

Work History