Adeolu M.

Key Skills

Software

Other

Top Subject Matter

AI data training and annotation (content, RLHF, preference labeling)

Multilingual content evaluation and translation verification

Voice over recording and audio labeling for AI training

Top Data Types

Text

Audio

Top Task Types

RLHF

Audio Recording

Freelancer Overview

AI data training and annotation (content writing tasks, RLHF, preference labelling). Core strengths include Other. Education includes Bachelor of Engineering @OAUSTECH. AI-training focus includes data types such as Text and Audio and labeling workflows including RLHF, Translation, and Localization.

Labeling Experience

Technical content review (engineering, science, and technology topics)

OtherText

Conducted technical content review to validate quality and correctness of engineering/science/technology material used in training or documentation contexts. Synthesized complex technical information into accurate, accessible written outputs. Supported reliable dataset content through editorial-style verification. • Technical review of engineering/science/tech content • Accuracy and clarity checks for written outputs • Synthesis of complex information into accessible text • Research-backed article writing for dataset/support material

2024 - Present

Voice over recording for AI training datasets, audio labelling, and speech samples

OtherAudioAudio Recording

Recorded and prepared voiceover/audio materials intended for AI training datasets and speech samples. Delivered studio-quality narration suitable for educational, commercial, and narrative applications. Performed audio labeling and review-oriented preparation to support downstream training. • Voice over recording for AI training datasets • Audio labeling and preparation of speech samples • Studio-quality narration delivery • Multi-language recording support

2024 - Present

Multilingual content evaluation and translation verification (AI training dataset readiness)

OtherText

Performed multilingual content evaluation and translation verification for AI training data readiness. Checked that translated/localized text matched original meaning and maintained clarity for target audiences. Supported accurate multilingual output to improve dataset reliability. • Translation verification for multilingual content • Content evaluation for accuracy and consistency • Localization-aware quality assurance • Linguistic alignment checks across languages

2024 - Present

AI data training and annotation (content writing tasks, RLHF, preference labelling)

OtherTextRLHF

Provided data training and annotation support for AI workflows, with a focus on RLHF-style preference labeling tasks. Produced high-quality content-writing outputs suitable for model training and evaluation. Ensured outputs were accurate and consistent with the intended linguistic and technical context. • Preference labeling for RLHF datasets • Content writing for AI training use cases • Preference data quality checks and consistency review • Multilingual/localization-aware output preparation

2024 - Present

Education

Work History