Miriam N.

Key Skills

Software

No software listed

Top Subject Matter

Human Activity Recognition

Autonomous Driving/Computer Vision

Computer Vision/Natural Language Processing

Top Data Types

Video

3D Sensor

Image

Top Task Types

Action Recognition

Bounding Box

Freelancer Overview

Data Labeller, Atlas Capture. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Business Information Technology, University of Nairobi (2022). AI-training focus includes data types such as Video, 3D Sensor, and Image and labeling workflows including Action Recognition and Bounding Box.

Labeling Experience

Corporate Trainer, Atlas Capture

VideoAction Recognition

I mentored a team of annotators focused on minimizing label ambiguity and increasing consistency. I developed and rolled out an optimized review pipeline for action timing and spatial awareness tasks. I provided targeted feedback and performance tracking to maintain high accuracy among team members. • Led specialized training in spatial awareness and temporal boundary detection. • Enforced rigorous adherence to annotation rubrics and captioning standards. • Established performance monitoring to reach 95%+ accuracy within weeks. • Oversaw workflow improvements that doubled validation speed without compromising quality.

2025 - Present

Data Annotator - LiDAR, Avala AI

3D SensorBounding Box

I created bounding boxes, polygons, and segmented objects such as vehicles and pedestrians in LiDAR point cloud data. I ensured object consistency across sequential frames and maintained high accuracy through rigorous quality assurance steps. I used proprietary annotation software to meet client project requirements. • Performed 3D annotation for vehicles, cyclists, and pedestrians. • Applied temporal tracking across multi-frame LiDAR data. • Participated in quality checks and peer review processes. • Escalated ambiguous cases to QA teams and documented edge cases.

2024 - Present

Data Labeller, Atlas Capture

VideoAction Recognition

I reviewed and refined model-generated video annotations focused on hand movements and object interactions. I validated and corrected action timing, ensuring each boundary aligned precisely with the start and end of activities. I assessed and edited captions to confirm atomicity and clarity for machine learning models. • Performed detailed frame-level analysis for annotation accuracy. • Edited and enforced standards for single-action captioning. • Enhanced quality of annotated video datasets for AI training. • Ensured precision in labeling temporal boundaries and object interactions.

2024 - Present

Data Annotation Specialist, Digital Divide Data (DDD)

ImageBounding Box

I used bounding boxes, polygons, keypoints, and semantic segmentation for annotating objects and scenes in images. I performed text sentiment labeling and fused 2D images with 3D LiDAR data to enhance multi-modal AI models. I achieved high accuracy in spatial and sentiment labeling using proprietary annotation tools. • Drew bounding boxes and polygons for cars, pedestrians, and complex shapes. • Mapped key points and performed semantic segmentation on images. • Labeled customer text data for sentiment classification. • Matched 2D images and 3D point clouds for data fusion tasks.

2024 - 2024

Education

Work History