Otieno W.

Key Skills

Software

Telus

Label Studio

LabelImg

Micro1

OneForma

Remotasks

Anno-Mage

Top Subject Matter

Autonomous driving

Nlp Domain Expertise

search relevance

Top Data Types

Video

Image

Audio

Top Task Types

Object Detection

Segmentation

RLHF

Transcription

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Bounding Box

Freelancer Overview

Data Annotation Specialist (Telus, Remote) — AI response evaluation and high-volume labeling. Core strengths include Telus, Internal, and Proprietary Tooling. Education includes Bachelor of Science, Pwani University (2020). AI-training focus includes data types such as Document and Video and labeling workflows including Evaluation, Rating, and Object Detection.

Labeling Experience

Data Annotation Specialist (Telus, Remote) — AI response evaluation and high-volume labeling

TelusDocument

Performed high-volume, guideline-driven data labeling across autonomous driving, NLP, and search relevance domains while maintaining top-tier quality scores. Evaluated AI-generated responses for factual accuracy, safety, and helpfulness to support RLHF improvements for large language models. Applied 50+ page technical guideline documents to ensure data consistency across global datasets. • Interpreted and followed complex project instructions • Produced gold-standard outputs prioritized for high-complexity tasks • Audited labeled data for adherence to specifications • Supported supervised machine learning and RLHF data preparation

2025 - 2025

Data Labeler and Curation Specialist (Fuzu, Remote) — Object detection labeling and dataset cleaning

VideoObject Detection

Tagged thousands of images and video frames for computer vision object detection in large-scale projects. Validated and cleaned legacy datasets by removing duplicates and correcting mislabeled entries used for internal training models. Identified and reported systematic errors in project instructions to refine workflows and improve throughput. • Conducted object detection labeling for images and video frames • Performed dataset curation and quality cleanup • Reported instruction issues to improve labeling accuracy • Maintained low rejection rates while meeting weekly targets

2023 - 2025

Education

Work History