Elija Lazaro

Key Skills

Software

Scale AI

Appen

Top Subject Matter

Data Labeling for AI/ML Pipelines

Video Annotation for AI Training

Linguistic Data Annotation and Verification

Top Data Types

Image

Video

Text

Top Task Types

Bounding Box

Action Recognition

Classification

Transcription

Freelancer Overview

Data Labeling Specialist. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Atlas Capture, Scale AI, and Crowdgen. Education includes Master of Arts, University of Dar es Salaam (2025) and Bachelor of Arts, University of Dodoma (2023). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Bounding Box, Action Recognition, and Classification.

Labeling Experience

Data Labeling Specialist

ImageBounding Box

As a Data Labeling Specialist using Atlas Capture, I performed structured data collection, image labeling, and annotation for AI/ML models. Tasks included bounding box, polygon segmentation, and classification, consistently meeting accuracy and throughput benchmarks. I contributed to data quality by flagging edge cases and annotating ambiguous instances per guidelines. • Conducted image and text annotation for machine learning pipelines. • Maintained a 99.2% accuracy rate with daily output targets. • Utilized Atlas Capture platform exclusively for all annotation workflows. • Ensured high consistency aligned with model training requirements.

As a Data Labeling Specialist using Atlas Capture, I performed structured data collection, image labeling, and annotation for AI/ML models. Tasks included bounding box, polygon segmentation, and classification, consistently meeting accuracy and throughput benchmarks. I contributed to data quality by flagging edge cases and annotating ambiguous instances per guidelines. • Conducted image and text annotation for machine learning pipelines. • Maintained a 99.2% accuracy rate with daily output targets. • Utilized Atlas Capture platform exclusively for all annotation workflows. • Ensured high consistency aligned with model training requirements.

2018 - Present

AI Data Trainer & Video/Annotation Specialist

Scale AIVideoAction Recognition

As an AI Data Trainer and Video/Annotation Specialist with Scale AI, I edited and corrected over 2,500 AI-generated annotations daily on multi-modal datasets. My focus included temporal labeling, action sequences, event tagging, and failure mode review, consistently achieving a 99.2% accuracy rate. I also contributed guideline feedback to improve downstream pipeline accuracy and efficiency. • Performed review and correction of AI model video and text outputs. • Executed prompt response scoring and cognitive evaluation for LLM/vision models. • Collaborated globally to standardize annotation best practices. • Ranked among the top 5% of annotators for accuracy and quality.

As an AI Data Trainer and Video/Annotation Specialist with Scale AI, I edited and corrected over 2,500 AI-generated annotations daily on multi-modal datasets. My focus included temporal labeling, action sequences, event tagging, and failure mode review, consistently achieving a 99.2% accuracy rate. I also contributed guideline feedback to improve downstream pipeline accuracy and efficiency. • Performed review and correction of AI model video and text outputs. • Executed prompt response scoring and cognitive evaluation for LLM/vision models. • Collaborated globally to standardize annotation best practices. • Ranked among the top 5% of annotators for accuracy and quality.

2023 - 2026

Senior Language & Data Specialist

TextClassification

As Senior Language & Data Specialist at Crowdgen, I managed up to 100 textual annotation and verification tasks daily, achieving a 97% satisfaction score over 18 months. I resolved contextual and semantic discrepancies and contributed to inter-annotator agreement. My proactive communication ensured standards and edge case handling across linguistic datasets. • Processed linguistic annotation and quality verification. • Focused on semantic and contextual accuracy in labeled datasets. • Improved annotation guidelines based on reviewer collaboration. • Achieved zero escalations across all confirmed tasks.

As Senior Language & Data Specialist at Crowdgen, I managed up to 100 textual annotation and verification tasks daily, achieving a 97% satisfaction score over 18 months. I resolved contextual and semantic discrepancies and contributed to inter-annotator agreement. My proactive communication ensured standards and edge case handling across linguistic datasets. • Processed linguistic annotation and quality verification. • Focused on semantic and contextual accuracy in labeled datasets. • Improved annotation guidelines based on reviewer collaboration. • Achieved zero escalations across all confirmed tasks.

2021 - 2022

Data Processing & Transcription Specialist

AppenTextTranscription

In the role of Data Processing & Transcription Specialist for Appen and Amazon Mechanical Turk, I categorized, annotated, and verified over 1,200 linguistic and behavioral data records per shift. I performed transcription, semantic categorization, and proactive error detection for client data QA. These contributions supported top-tier accuracy and expedited batch processing timelines. • Performed high-volume linguistic transcription and record labeling. • Maintained 100% quality audit pass rate throughout tenure. • Completed tasks significantly faster than team average. • Reduced rework time through early detection of annotation inconsistencies.

In the role of Data Processing & Transcription Specialist for Appen and Amazon Mechanical Turk, I categorized, annotated, and verified over 1,200 linguistic and behavioral data records per shift. I performed transcription, semantic categorization, and proactive error detection for client data QA. These contributions supported top-tier accuracy and expedited batch processing timelines. • Performed high-volume linguistic transcription and record labeling. • Maintained 100% quality audit pass rate throughout tenure. • Completed tasks significantly faster than team average. • Reduced rework time through early detection of annotation inconsistencies.

2019 - 2021

Education

Work History