Sheriff A.

Key Skills

Software

Labelbox

Appen

OneForma

Toloka

Internal/Proprietary Tooling

Top Subject Matter

Nlp Domain Expertise

LLM fine-tuning

Rlhf Domain Expertise

Top Data Types

Text

Image

Document

Top Task Types

Entity (NER) Classification

Object Detection

Question Answering

Data Collection

Transcription

Text Generation

Freelancer Overview

Over the past three years, I've worked across platforms including Appen, Toloka, Scale AI, and Remotasks, completing upwards of 12,000 individual annotation tasks across a wide range of project types, from text classification and named entity recognition to image labelling, audio transcription, and prompt-response evaluation for large language models. I'm comfortable working with detailed annotation guidelines, consistently maintaining QA approval rates of 90–96%, and flagging edge cases that would otherwise slip through. I've also contributed to RLHF pipelines across two long-term projects, ranking and rating model outputs based on accuracy, helpfulness, and safety which means I understand not just what good labelled data looks like, but why it matters to the models being trained. What sets me apart is the combination of hands-on annotation experience with a technical background in computer science and web development. Across roughly four years of freelance and contract work, I've delivered on over 15 distinct projects spanning NLP, computer vision, and conversational AI datasets. I know how software is built, which helps me understand the downstream impact of the data I produce. I'm detail-oriented by nature, consistent under repetitive workloads, and I take data quality seriously. I've always treated every label as something that will travel further than the task I'm sitting on.

Labeling Experience

DataLabeller & AITrainer (Freelance) — Freelance (Remote/Contract)

LabelboxTextEntity (NER) Classification

Freelance DataLabeller and AI Trainer annotated text-based datasets to support supervised learning for multiple clients. Work included intent recognition and entity extraction, plus quality checks to ensure annotation consistency. Responsible for maintaining accuracy standards and flagging edge cases for lead review. • Completed prompt-response evaluation tasks for LLM fine-tuning, ranking outputs by accuracy, helpfulness, and safety guidelines. • Maintained inter-annotator agreement scores above X% across extended projects and escalated edge cases. • Participated in RLHF feedback rounds by assessing model-generated responses against detailed rubrics. • Annotated diverse text datasets for downstream NLP pipeline training and evaluation.

2024 - Present

AI Data Annotator — LinksyAI (Remote/Contract)

TextEntity (NER) Classification

Worked as an AI Data Annotator tagging and classifying text for NLP model training under changing project guidelines. Performed quality assurance by reviewing peer annotations and verifying that outputs met defined accuracy standards. Adapted quickly to domain-specific instructions spanning e-commerce, healthcare, and conversational AI. • Tagged and classified text data for intent recognition and entity extraction tasks. • Reviewed and quality-checked annotation batches produced by peer annotators. • Maintained project accuracy standards through verification and consistency checks. • Adapted to evolving annotation guidelines across multiple domains.

2024 - 2025

Education

Work History