Seun J.

Key Skills

Software

Remotasks

Top Subject Matter

Large language model (LLM) response evaluation and RLHF-style feedback for multilingual prompts

NLP annotation for NER

Sentiment Domain Expertise

Top Data Types

Text

Image

Top Task Types

Classification

Freelancer Overview

AI Data Trainer & Evaluator (Outlier.ai, Remote). Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Outlier.ai, Remotasks, and Internal. Education includes Bachelor of Science, University of Lagos (2022) and Certificate, DeepLearning.AI (Coursera) (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Entity (NER).

Labeling Experience

AI Data Trainer & Evaluator (Outlier.ai, Remote)

Text

Evaluated and ranked AI-generated responses for quality, accuracy, and instruction-following across text, coding, and reasoning tasks in an LLM feedback workflow. Wrote and refined prompts to probe model capabilities and elicit weaknesses in edge cases. Provided detailed written feedback and justifications to support model alignment with human expectations. • Response ranking and quality scoring • Prompt writing and adversarial/edge-case testing • Written feedback with rating justifications • Multilingual evaluation for English and Yoruba content

2023 - Present

Freelance Data Annotator (Remotasks, Remote)

RemotasksText

Annotated text datasets for named entity recognition, sentiment analysis, and intent classification tasks within remote annotation projects. Labeled and reviewed image-text pairs to support multimodal AI training. Followed onboarding workshops and annotation guideline reviews to maintain consistency and project accuracy. • NER labeling on text datasets • Sentiment and intent classification labeling • Multimodal image-text pair review • Compliance with annotation guidelines and QA

2023 - 2023

Data Science Intern (Terragon Group, Lagos)

TextClassification

Supported labeling efforts for customer segmentation and NLP classification projects using internal annotation tools. Assisted with cleaning and preprocessing raw datasets used for supervised machine learning training pipelines. Prepared dataset quality summary reports and flagged inconsistencies for senior team review. • Assisted labeling for customer segmentation • Supported NLP classification data labeling • Dataset preprocessing and QA support • Reported dataset quality metrics and inconsistencies

2022 - 2022

Education

Work History