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Akinlabi A.

AI Research & Annotation Specialist (TURING) — RLHF preference ranking and rubric-based evaluation

United Kingdom flagN/A, England

Key Skills

Software

Other

Top Subject Matter

AI evaluation
LLM training data annotation
RLHF workflow calibration

Top Data Types

TextText
VideoVideo
DocumentDocument

Top Task Types

RLHFRLHF

Freelancer Overview

AI Research & Annotation Specialist (TURING) — RLHF preference ranking and rubric-based evaluation. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Arts, University of Toronto and Bachelor of Arts, University of Waterloo. AI-training focus includes data types such as Text and Video and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

AI Research & Annotation Specialist (TURING) — RLHF preference ranking and rubric-based evaluation

OtherTextTextRLHFRLHF

Conducted advanced data annotation and RLHF preference ranking for analytical and long-form English outputs while maintaining 99% guideline compliance across calibration cycles. Applied rubric-based scoring to assess clarity, coherence, logical reasoning integrity, factual grounding, and instruction adherence. Performed iterative QA audits including hallucination detection, source validation, and chain-of-thought reasoning reviews to improve reliability and reasoning metrics. • RLHF preference ranking for English analytical/long-form outputs • Rubric evaluation for clarity, coherence, reasoning integrity, factuality, and constraint adherence • Hallucination detection and source validation audits • Markdown documentation delivery in Slack to reduce review turnaround

2025 - 2026

Multimodal Evaluation & Content Systems Specialist (REWRKIT) — video/visual evaluation and rating

OtherVideoVideo

Evaluated AI-generated visual and video outputs for temporal consistency, object persistence, and prompt-to-output alignment to identify continuity errors. Conducted visual fidelity audits including distortion, frame instability, and color inconsistencies, and performed motion blur and frame-sequence stability checks. Simulated real production conditions using Canva and CapCut to improve evaluation realism and inter-reviewer agreement. • Temporal consistency and continuity error detection for video outputs • Visual fidelity auditing and artifact identification • Motion blur analysis and frame sequence stability checks • Prompt-to-output constraint adherence validation in multimodal tasks

2023 - 2024

Education

S

Seneca Polytechnic

Graduate Certificate, Data Analytics & AI Strategy

Graduate Certificate
Not specified
U

University of Waterloo

Bachelor of Arts, Honours English & Professional Writing

Bachelor of Arts
Not specified

Work History

T

Turing

AI Content Evaluation & Research Specialist

N/A
2025 - 2026
R

Rewrkit

Multimodal Evaluation & Content Systems Specialist

N/A
2023 - 2024