Rilwan M.

Key Skills

Software

Other

Top Subject Matter

AI video clipping

transcription-aware content segmentation

AI-driven summarization and narration for video clips

Top Data Types

Video

Top Task Types

Routing

Text Summarization

Segmentation

Entity (NER) Classification

Freelancer Overview

Software Developer & Product Owner - NeoMidas. Brings 13+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, Kogi State University. AI-training focus includes data types such as Video and labeling workflows including Routing, Text Summarization, and Segmentation.

Labeling Experience

Software Developer & Product Owner - NeoMidas

VideoSegmentationEntity (NER) Classification

As a Software Developer and Product Owner, you designed and productized an AI-powered video clipping application for multiple content categories. You led implementation of content routing and transcript-aware clip refinement while managing the full product lifecycle from architecture to iteration. The role required software/product ownership skills, applied AI tool integration, and strong documentation for effective developer handoffs. • Designed AI video clipping supporting 12+ content categories including interviews and educational segments • Implemented diarization-based routing, topic segmentation, and scene boundary detection for cinematic edits • Integrated Whisper for transcript-aware boundary refinement and selected Piper for local TTS narration • Managed developer handoff documentation and iterative product development from planning to release

2022 - Present

Software Developer & Product Owner | NeoMidas (AI Video Clipping Tool) (2022 – Present)

OtherVideoRoutingText Summarization

Developed an AI video clipping application that processes multiple content categories using automated content-type routing. Implemented diarization for interviews and topic segmentation for educational content to determine how clips should be generated. Refined clip boundary outputs using transcript-aware processing for more accurate segmentation and narration. • Speaker diarization–based routing for interview content • Topic segmentation for educational categories • Scene boundary detection for cinematic clips • Whisper-based transcript refinement to improve clip boundaries

2022 - Present

Education

Work History