Kelvin L.

Key Skills

Software

Remotasks

Top Subject Matter

Autonomous driving

3D LiDAR point clouds

Computer vision

Top Data Types

3D Sensor

Video

Audio

Image

Text

Document

Top Task Types

Point/Key Point

Tracking

Transcription

Freelancer Overview

AI Data Specialist (LiDAR) – Remote (Remotasks). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Remotasks. Education includes Bachelor of Science with Honours, University of Edinburgh. AI-training focus includes data types such as 3D Sensor, Video, and Audio and labeling workflows including Point, Key Point, and Tracking.

Labeling Experience

AI Data Specialist (Transcription) – Remote (Remotasks)

RemotasksAudioTranscription

Worked on transcription tasks involving audio and text data to enable AI training pipelines. Produced accurate transcriptions while applying strict consistency rules. Followed QA guidelines with repeated checking before final submission. • Transcribed audio into text for training data • Validated consistency between audio and resulting text • Rechecked outputs against QA guidelines • Maintained high accuracy (95%+ expected)

2022 - 2022

AI Data Specialist (2D Video Labelling) – Remote (Remotasks)

RemotasksVideoTracking

Completed 2D video labeling tasks including tracking objects and assigning frame-wise labels for computer vision datasets. Maintained high labeling quality by carefully checking outputs prior to QA submission. Supported dataset creation for computer vision training pipelines. • Tracked objects across frames in video • Produced frame-wise labels for CV datasets • Performed careful pre-submission QA validation • Maintained accuracy targets (95%+ )

2022 - 2022

AI Data Specialist (LiDAR) – Remote (Remotasks)

Remotasks3D SensorPoint/Key Point

Performed 3D LiDAR annotation for autonomous driving model training by annotating objects in point cloud data. Applied consistent labeling practices to support reliable machine learning inputs. Followed quality checks to maintain accuracy above QA thresholds. • Annotated objects within point cloud data • Ensured labeling consistency across large datasets • Verified work against QA guidelines before submission • Focused on accuracy (95%+ expected)

2022 - 2022

Education

Work History