Julius O.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

LLM training data creation and AI content quality (generalist domains)

Environmental science field datasets (geospatial/research data)

Environmental field study data preparation (geospatial/research data)

Top Data Types

Text

Document

Top Task Types

Data Collection

Freelancer Overview

Generalist AI Trainer & Content Quality Specialist (Freelance/Independent Contractor). Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Don't disclose and Other. Education includes Master of Science, University of California, Los Angeles (UCLA) (2023) and Bachelor of Science, University of Southern California (USC). AI-training focus includes data types such as Text, Geospatial, and Tiled Imagery and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Generalist AI Trainer & Content Quality Specialist (Freelance/Independent Contractor)

Don't discloseText

Authored and refined 1,000+ prompts and AI model responses to build high-quality LLM training datasets. Evaluated and ranked AI outputs for accuracy, tone, style, safety, and logical coherence while delivering structured constructive feedback to meet complex project guidelines. Performed adversarial testing and multi-source fact-checking to reduce error rates and improve dataset reliability over iterative cycles. • Produced prompt and response materials for diverse domains (STEM, humanities, law, finance, history, arts) • Ranked and rated model outputs with attention to safety and risk identification • Applied evolving annotation/guideline requirements with rapid workflow adaptation • Developed analytical prompts supporting RLHF pipelines to improve comprehension and coherence scores

2018 - Present

Data & Research Assistant | CIFOR-ICRAF

OtherData Collection

Collected, validated, and analyzed field datasets using electronic data capture systems to improve data accuracy versus prior collection cycles. Supported model calibration and quantitative reporting by applying analytical reasoning across multi-variable environmental and economic research scenarios. Maintained rigorous documentation standards across multiple regional teams to ensure clean, usable datasets for downstream work. • Collected and validated structured field data with electronic data capture tools • Contributed to quantitative reporting and model calibration activities • Ensured dataset integrity through cleaning and careful documentation • Coordinated with cross-functional stakeholders across regional teams

2023 - 2023

Research Support Analyst | The Nature Conservancy

OtherData Collection

Supported data collection, cleaning, and analysis for two pilot environmental field studies. Maintained analytical data logs and documentation workflows to enable reliable handoff to senior researchers with zero data loss incidents. Ensured dataset integrity for accurate downstream quantitative reporting. • Collected and cleaned pilot study datasets • Maintained data logs and documentation for research handoff • Supported analytical workflows for environmental measurements • Ensured integrity of datasets used in quantitative reporting

2022 - 2022

Education

Work History