Doris Odogun

Key Skills

Software

Toloka

Micro1

Mercor

Top Subject Matter

Computer Vision and Speech Processing

Video Data Annotation for AI Training

Large Language Model (LLM) Training and Evaluation

Top Data Types

Video

Text

Image

Top Task Types

Object Detection

Bounding Box

RLHF

Entity (NER) Classification

Freelancer Overview

Video, Audio & Data Annotator. Core strengths include Toloka, Micro1, and Mercor. Education includes Bachelor of Science, Delta State University. AI-training focus includes data types such as Video and Text and labeling workflows including Object Detection, Bounding Box, and RLHF.

Labeling Experience

Video, Audio & Data Annotator

TolokaVideoObject Detection

As a video, audio, and data annotator at Toloka AI, I conducted annotations on video datasets, focusing on object detection, scene classification, and action recognition. I labeled audio recordings for speech recognition, speaker identification, and sound event detection, aligning with strict accuracy and turnaround standards. Reviewing and validating other contributors' annotations was also a key part of my role. • Performed object detection, scene classification, and action recognition on video datasets. • Labeled and tagged audio for speech recognition and event identification. • Maintained high accuracy and met strict turnaround requirements. • Reviewed and validated peer annotations for adherence to quality standards.

As a video, audio, and data annotator at Toloka AI, I conducted annotations on video datasets, focusing on object detection, scene classification, and action recognition. I labeled audio recordings for speech recognition, speaker identification, and sound event detection, aligning with strict accuracy and turnaround standards. Reviewing and validating other contributors' annotations was also a key part of my role. • Performed object detection, scene classification, and action recognition on video datasets. • Labeled and tagged audio for speech recognition and event identification. • Maintained high accuracy and met strict turnaround requirements. • Reviewed and validated peer annotations for adherence to quality standards.

2023 - Present

Data-Video Generalist / Annotator

Micro1VideoBounding Box

At Micro1, I delivered multimodal video annotation services including bounding box, keypoint labeling, and temporal segmentation. My work supported AI training pipelines by supplying clean, well-labeled video, audio, and text data through adherence to strict annotation guidelines. Consistently high-quality scores were maintained in each annotation project assigned. • Annotated videos with bounding boxes, keypoints, and temporal segments. • Adapted quickly to new data annotation schema updates. • Contributed to multiple multimodal AI training pipelines. • Held high quality and accuracy scores across projects.

At Micro1, I delivered multimodal video annotation services including bounding box, keypoint labeling, and temporal segmentation. My work supported AI training pipelines by supplying clean, well-labeled video, audio, and text data through adherence to strict annotation guidelines. Consistently high-quality scores were maintained in each annotation project assigned. • Annotated videos with bounding boxes, keypoints, and temporal segments. • Adapted quickly to new data annotation schema updates. • Contributed to multiple multimodal AI training pipelines. • Held high quality and accuracy scores across projects.

2022 - 2024

Data Annotator

MercorTextRLHF

At Mercor, I labeled diverse text, image, and code datasets to support large language models and model evaluation. This included prompt writing, response rating, and reinforcement learning from human feedback (RLHF) tasks. My work contributed to iterative model refinement cycles and maintained high accuracy rates across various annotation assignments. • Annotated text, image, and code datasets for AI model improvement. • Created prompts and rated LLM outputs following RLHF processes. • Provided quality feedback for continuous model enhancement. • Maintained above-threshold accuracy in multitask annotation projects.

At Mercor, I labeled diverse text, image, and code datasets to support large language models and model evaluation. This included prompt writing, response rating, and reinforcement learning from human feedback (RLHF) tasks. My work contributed to iterative model refinement cycles and maintained high accuracy rates across various annotation assignments. • Annotated text, image, and code datasets for AI model improvement. • Created prompts and rated LLM outputs following RLHF processes. • Provided quality feedback for continuous model enhancement. • Maintained above-threshold accuracy in multitask annotation projects.

2021 - 2023

Data Annotator

TextEntity Ner Classification

At Kled AI, I performed entity recognition, text classification, and sentiment annotation on diverse datasets for AI model development. My role required adapting to shifting guidelines while ensuring timely delivery of labeled data batches. I also conducted thorough quality checks and flagged inconsistencies for review to maintain project standards. • Conducted entity recognition, classification, and sentiment tagging for AI use cases. • Adapted annotation process as guidelines evolved across projects. • Delivered data batches promptly to meet deadlines. • Reviewed and flagged inconsistencies to uphold annotation quality.

At Kled AI, I performed entity recognition, text classification, and sentiment annotation on diverse datasets for AI model development. My role required adapting to shifting guidelines while ensuring timely delivery of labeled data batches. I also conducted thorough quality checks and flagged inconsistencies for review to maintain project standards. • Conducted entity recognition, classification, and sentiment tagging for AI use cases. • Adapted annotation process as guidelines evolved across projects. • Delivered data batches promptly to meet deadlines. • Reviewed and flagged inconsistencies to uphold annotation quality.

2020 - 2022

Education

Work History