Joshua A.

Key Skills

Software

SuperAnnotate

Don't disclose

Top Subject Matter

Ubuntu/Linux AI data training and evaluation

LLM prompt evaluation and AI output quality scoring

Structured data parsing and quality control for AI workflows

Top Data Types

Text

Image

Document

Top Task Types

Function Calling

Freelancer Overview

AI Data Training Contractor (Ubuntu/Linux Specialist) — SME Careers / SuperAnnotate. Brings 4+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include SuperAnnotate and Don't disclose. Education includes Bachelor of Science, Osun State University (2024) and IBM AI Engineering Specialization, Coursera (2024). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Function Calling.

Labeling Experience

AI Data Training Contractor (Ubuntu/Linux Specialist) — SME Careers / SuperAnnotate

SuperAnnotateText

Ubuntu/Linux AI data training contractor performing quality assessment of AI-generated outputs in a Linux context. Evaluates responses for correctness, safety, and instruction adherence using domain knowledge of shell scripting and command-line operations. Produces labeling decisions that support model training dataset readiness across Linux/Ubuntu tasks. • Labels and reviews AI outputs in an Ubuntu/Linux environment • Performs quality checks against correctness, safety, and instruction-following criteria • Applies shell scripting and file-system knowledge to verify technical accuracy • Ensures annotated outputs meet training-data standards

2025 - Present

Freelance AI Workflow Automation Engineer — Independent

Don't discloseTextFunction Calling

Freelance workflow automation engineer focused on structured data handling and systematic data quality review. Builds pipelines that parse and validate structured formats while maintaining consistent label application across multiple concurrent data sources. Applies quality-control logic comparable to professional annotation and labeling review processes. • Worked with structured JSON, XML, and RSS in automation workflows • Managed data integrity issues including deduplication and format normalization • Operated Ubuntu server environments for production pipelines and QA • Ensured consistent labeling application across multiple data sources using QC logic

2023 - Present

AI Prompt Evaluator & LLM Output Reviewer — Independent Practice

Don't discloseText

Independent AI prompt evaluator and LLM output reviewer scoring hundreds of model responses across multiple providers. Assesses coherence, relevance, factual grounding, hallucination risk, instruction-following, and formatting compliance. Uses rubric-driven evaluation and iterative prompt-template refinement to improve output quality and calibration. • Quality-scored LLM outputs from Groq (Llama), Google Gemini, Anthropic Claude, and Llama • Designed and refined prompt templates for scoring structured JSON and free text • Evaluated resume-tailoring and job-filtering outputs for alignment to original instructions • Manually reviewed model scores and labels to correct misclassifications and improve precision

2023 - Present

Education

Work History