Sosanwo A.

Key Skills

Software

Labelbox

Scale AI

Top Subject Matter

Agronomy & Soil Science (Agricultural computer vision)

Crop health diagnosis (computer vision)

Top Data Types

Video

Image

Top Task Types

RLHF

Segmentation

Freelancer Overview

AI Training & Content Specialist (Independent/Project-Based). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OBS Studio, Camtasia, and Labelbox. Education includes Bachelor of Agriculture, University of Ilorin. AI-training focus includes data types such as Video and Image and labeling workflows including RLHF and Segmentation.

Labeling Experience

AI Training & Content Specialist (Independent/Project-Based)

LabelboxImageSegmentation

Performed semantic segmentation and object detection labeling on large-scale agricultural datasets to improve AI accuracy in crop health diagnosis. Ensured labeled outputs supported downstream model training for recognizing agricultural patterns from visual inputs. Produced high-quality, consistent annotations aligned with scientific interpretation of crop conditions. • Completed segmentation/object detection labeling for agricultural imagery • Improved crop health diagnosis model accuracy via dataset refinement • Applied scientific domain context to annotation quality • Supported training readiness through labeling and quality assurance practices

2024 - Present

AI Training & Content Specialist (Independent/Project-Based)

VideoRLHF

Recorded and edited high-fidelity video tutorials and demonstrations to train computer vision models for agricultural workflows and pattern recognition. Provided RLHF-style human feedback to improve model behavior for STEM and technical use cases, aligning outputs with factual scientific requirements. Supported iterative AI training loops by combining instructional media with structured feedback from domain expertise. • Produced instructional video content for AI training scenarios in agriculture • Calibrated responses for factual accuracy in scientific and data-driven contexts • Used video footage to support comparative analysis and training refinement • Applied domain knowledge to guide training outcomes in technical workflows

2024 - Present

Education

Work History