Progress O.

Key Skills

Software

Don't disclose

SuperAnnotate

Top Subject Matter

Speech recognition and audio-to-text dataset quality assurance

Autonomous systems video annotation QA

Natural language processing dataset engineering

Top Data Types

Audio

Video

Text

Image

Document

Top Task Types

Transcription

Tracking

Entity (NER) Classification

Action Recognition

Data Collection

Freelancer Overview

Senior Data Annotation & QA Specialist | SAFEWOX (Remote). Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and SuperAnnotate. Education includes Higher National Diploma, Institution Verified. AI-training focus includes data types such as Audio, Video, and Text and labeling workflows including Transcription, Tracking, and Entity (NER) Classification.

Labeling Experience

Senior Data Annotation & QA Specialist | SAFEWOX (Remote)

SuperAnnotateVideoTracking

Performed computer vision validation by supervising frame-by-frame visual tracking and event tagging on dense, multi-layer video objects for autonomous system training analytics. Ensured accuracy of temporal/event annotations by cross-checking outputs against evolving project guidelines under production timelines. Focused on high-complexity visual QA to support model training for autonomous driving analytics. • Frame-by-frame visual tracking supervision• Event tagging on dense multi-layer video objects• High-precision QA against dynamic guidelines• Support for autonomous system training analytics pipelines

2022 - 2026

Senior Data Annotation & QA Specialist | SAFEWOX (Remote)

Don't discloseAudioTranscription

Calibrated multilingual audio data by performing speech transcriptions and tracking acoustic sound characteristics for training speech recognition models. Implemented a secondary-tier validation protocol to mitigate entry errors and improve dataset reliability for downstream ML workflows. Coordinated with ML engineering teams to review edge cases and iteratively update annotation and QA procedures across active pipelines. • Multilingual speech file transcription and acoustic characterization• Secondary validation tier to reduce error rates by 20%• QA collaboration with ML teams on model edge cases• Technical onboarding and guideline enforcement for junior annotators

2022 - 2026

Linguistic & Text Data Annotator | AFC Consulting (Remote)

Don't discloseAudioData Collection

Processed and categorized thousands of distinct audio files to optimize automated voice-to-text algorithms. Verified audio inputs for consistency and usability before they were used in training pipelines. Standardized and cleaned multilingual audio datasets including complex dialect variations and non-linguistic filler sounds. • Audio processing and systematic categorization• Verification of audio inputs for voice-to-text optimization• Standardization and cleaning of complex multilingual audio• Preparation of optimized audio inputs for automated transcription models

2018 - 2022

Linguistic & Text Data Annotator | AFC Consulting (Remote)

Don't discloseVideoAction Recognition

Produced continuous, precisely segmented video annotations mapping vehicle classifications and obstacle parameters to support autonomous vehicle training. Implemented consistent segmentation and labeling quality controls to ensure labeled footage met dataset requirements for model development. Coordinated labeling outputs to reflect evolving criteria while sustaining delivery schedules. • Segmented video annotations for autonomous vehicle training• Vehicle classification and obstacle parameter mapping• Quality-controlled, continuous annotation production• Compliance alignment with evolving dataset criteria

2018 - 2022

Linguistic & Text Data Annotator | AFC Consulting (Remote)

Don't discloseTextEntity (NER) Classification

Engineered NLP datasets by extracting raw text corpora and applying entity classification and fine-grained sentiment labeling for linguistic model training. Carried out systematic verification of labeling outputs to support accurate training data for advanced NLP architectures. Maintained compliance with labeling criteria via daily random sampling checks on production outputs. • Entity classification and sentiment labeling on large text corpora• Verification of NLP labeling outputs for model training• Daily random sampling guideline compliance auditing• Preparation of structured data for linguistic model development

2018 - 2022

Education

Work History