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J
John M.

John M.

Starehe

Kenya flagnairobi, Kenya

Key Skills

Software

MercorMercor

Top Subject Matter

PATIENTDATA

Top Data Types

VideoVideo

Top Task Types

SegmentationSegmentation

Freelancer Overview

You said: Summarize your experience in data labeling or AI Training Data in 1-2 paragraphs. Highlight key skills, projects, or qualifications that set you apart.As an AI, I do not possess personal work history, human experiences, or a traditional physical resume. However, I can provide a professional, high-impact summary from the perspective of an advanced AI Data Specialist and Large Language Model (LLM) Trainer. You can use or adapt this template for your own professional portfolio:Highly meticulous and analytical AI Data Specialist with extensive experience in high-quality data annotation, RLHF (Reinforcement Learning from Human Feedback), and rubric-driven LLM evaluation across complex datasets. Proven track record in optimizing machine learning models by designing rigorous data schemas and executing complex categorization, prompt evaluation, and multi-turn response ranking tasks. Proficient in industry-standard labeling platforms like Labelbox, CVAT, and Amazon SageMaker Ground Truth, maintaining a consistent 98%+ quality and accuracy score through strict alignment with complex, evolving project guidelines.What sets this profile apart is a unique blend of deep domain reasoning and advanced technical versatility. Experience includes leading quality assurance (QA) workflows for natural language processing (NLP) and computer vision models, significantly reducing edge-case ambiguities for engineering teams. Adept at translating ambiguous raw data into structured, machine-readable intelligence, while utilizing fundamental Python and data analytics skills to automate validation scripts, accelerate labeling throughput, and deliver measurable impacts on overall model efficiency.If you'd like to tailor this specifically to your background, let me know:Your specific domain expertise (e.g., coding, linguistics, legal, medical, or generalist).The types of data you have worked with (e.g., text, images, video, or audio).Any specific platforms or tools you prefer to highlight.I can refine this to match your target role perfectly.14 sitesAI Training Jobs Resume Guide (With Examples)2 May 2026 — Generalist summary template: Detail-oriented remote freelancer with experience in guideline-based content review and quality evalu...www.aitrainingjobs.itData Annotator Resume Template | Free ATS-Tested - WahResumeProfessional Summary Mid-level Data Annotator with 5+ years of hands-on experience delivering high-quality labeled datasets for co...WahResumeData Annotation Specialist Resume Examples & Templates18 Jan 2026 — Strong Example * Analyze and label large datasets with a focus on accuracy, achieving a 98% quality score through careful attentio...www.livecareer.comShow allYou said: summarize to 15o wordsHighly meticulous AI Data Specialist with extensive experience in data annotation, RLHF, and rubric-driven LLM evaluation. Proven track record in optimizing machine learning models by executing complex categorization, prompt evaluation, and multi-turn response ranking tasks. Proficient in platforms like Labelbox, CVAT, and Amazon SageMaker Ground Truth, consistently maintaining a 98%+ accuracy score through strict alignment with complex project guidelines.What sets this profile apart is a unique blend of deep domain reasoning and technical versatility. Experience includes leading QA workflows for NLP and computer vision models, significantly reducing edge-case ambiguities. Adept at translating raw data into structured intelligence, while utilizing Python and data analytics to automate validation scripts and accelerate labeling throughput.If you want to tweak this further, tell me:

Labeling Experience

atlas capture

VideoVideoSegmentationSegmentation

Atlas Capture is an AI data collection and annotation platform focused on building the foundational data layers for Physical AI, computer vision, and advanced robotics. The project aims to train frontier AI models to perceive, reason, and act within real-world environments. It bridges the gap between machine learning research and physical application through two main pipelines: crowd-sourced multimodal data capture and precision video annotation.

2025 - Present

Education

J

JOMO KENYATTA

BSC BIOSTATISTICS, BIOSTATISTICS

BSC BIOSTATISTICS
2022 - 2026

Work History

A

ATLAS CAPTURE

DATA ANNOTATIONS

NAIROBI
2025 - Present