For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

Invite to Job
J
Joshua Anjorin

Joshua Anjorin

AI Training Data Specialist (SFT, Prompt Engineering & NLP)

Nigeria flagAkure, Nigeria
$25.00/hrExpertOtherHivemindMindrift

Key Skills

Software

Other
HiveMindHiveMind
MindriftMindrift
TolokaToloka
Internal/Proprietary Tooling

Top Subject Matter

Language Data/Audio Linguistics
Artificial Intelligence / Machine Learning
Natural Language Processing

Top Data Types

AudioAudio
TextText
Computer Code ProgrammingComputer Code Programming

Top Task Types

Emotion RecognitionEmotion Recognition
Text GenerationText Generation
Computer Programming/CodingComputer Programming/Coding
Evaluation/RatingEvaluation/Rating
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)

Freelancer Overview

Contributor, Data Annotation and Alignment. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Engineering, University of Ibadan (2024) and Professional Certification in Data Science, Future Academy Africa (2019). AI-training focus includes data types such as Audio and labeling workflows including Emotion Recognition.

ExpertEnglishYorubaHausa

Labeling Experience

Data Annotation Specialist

TextPrompt Response Writing SFT
Contributed to AI training workflows by designing and preparing high quality text datasets used for supervised fine tuning of language models. Developed structured prompt response datasets by transforming raw data into clear, context rich inputs aligned with model training objectives. Collaborated with data annotators and machine learning engineers to refine response quality, ensure consistency in tone and reasoning, and align outputs with expected model behavior. Implemented data cleaning, validation, and formatting processes to improve the accuracy and usability of training data across multiple NLP use cases Supported quality assurance efforts by reviewing generated responses, identifying inconsistencies, and improving dataset reliability for downstream AI model performance. Processed and managed large scale text data from multiple sources, ensuring scalability and efficiency in AI training pipelines.

Contributed to AI training workflows by designing and preparing high quality text datasets used for supervised fine tuning of language models. Developed structured prompt response datasets by transforming raw data into clear, context rich inputs aligned with model training objectives. Collaborated with data annotators and machine learning engineers to refine response quality, ensure consistency in tone and reasoning, and align outputs with expected model behavior. Implemented data cleaning, validation, and formatting processes to improve the accuracy and usability of training data across multiple NLP use cases Supported quality assurance efforts by reviewing generated responses, identifying inconsistencies, and improving dataset reliability for downstream AI model performance. Processed and managed large scale text data from multiple sources, ensuring scalability and efficiency in AI training pipelines.

2024 - 2026

Contributor, Data Annotation and Alignment

OtherAudioEmotion Recognition
Annotated and aligned large audio data with written transcripts using structured tagging systems. Labeled linguistic features such as emotions, parts of speech, and contextual nuances to improve dataset quality for machine learning. Processed and classified large volumes of language data, contributing to improved AI model training accuracy. • Annotated hundreds of third party company audio files and matched them with corresponding transcripts. • Utilized structured tagging systems to ensure consistent and high-quality data labeling. • Enhanced the reliability and richness of language training datasets. • Improved AI model performance by ensuring accurate alignment and nuanced linguistic classification.

Annotated and aligned large audio data with written transcripts using structured tagging systems. Labeled linguistic features such as emotions, parts of speech, and contextual nuances to improve dataset quality for machine learning. Processed and classified large volumes of language data, contributing to improved AI model training accuracy. • Annotated hundreds of third party company audio files and matched them with corresponding transcripts. • Utilized structured tagging systems to ensure consistent and high-quality data labeling. • Enhanced the reliability and richness of language training datasets. • Improved AI model performance by ensuring accurate alignment and nuanced linguistic classification.

2022 - 2022

Education

U

University of Ibadan

Bachelor of Engineering, Electrical and Electronics Engineering

Bachelor of Engineering
2020 - 2024
F

Future Academy Africa

Professional Certification in Data Science, Data Science

Professional Certification in Data Science
2019 - 2019

Work History

T

Transperfect

Data Engineer

London
2024 - 2026
P

Panoraworks

Senior Software Engineer

Ikeja
2019 - 2024