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Christina F

Christina F

AI Trainer, Cybersecurity Expert | Handshake AI Fellowship

USA flagTampa, FL, Usa
IntermediateInternal Proprietary ToolingDon T DiscloseOther

Key Skills

Software

Internal/Proprietary Tooling
Don't disclose
Other
Micro1

Top Subject Matter

Cybersecurity Domain Expertise
General Knowledge
Multimodal AI

Top Data Types

Computer Code ProgrammingComputer Code Programming
TextText
ImageImage
AudioAudio
DocumentDocument

Top Task Types

Bounding BoxBounding Box
ClassificationClassification
Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection
Evaluation/RatingEvaluation/Rating
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
Question AnsweringQuestion Answering
Red TeamingRed Teaming
Text GenerationText Generation
Text SummarizationText Summarization
TranscriptionTranscription
Translation/LocalizationTranslation/Localization
SegmentationSegmentation

Freelancer Overview

AI Trainer, Cybersecurity Expert | Handshake AI Fellowship. Brings 16+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other and micro1. Education includes Master of Science, Western Governors University (2025) and Certificate, SANS Women's Immersion Academy (2022). AI-training focus includes data types such as Text, Image, and Audio and labeling workflows including Evaluation, Rating, and Segmentation.

IntermediateEnglish

Labeling Experience

AI Trainer, Audio & Linguistics Expert/Cybersecurity Domain Expert | micro1

Micro1Audio
As an AI Trainer at micro1, I evaluate and annotate AI-generated audio samples for clarity, naturalness, and technical accuracy. I conduct detailed comparisons of synthetic voices, benchmark speech against human standards, and provide feedback for TTS model improvement. My work ensures consistency, reliability, and improved quality in AI speech output across languages and prompts. • Performed waveform and spectrogram analysis for speech quality • Identified and documented mispronunciations and anomalies in audio output • Assessed phonetic accuracy, pitch, and timing in generated speech • Flagged inconsistencies to improve overall TTS model reliability

As an AI Trainer at micro1, I evaluate and annotate AI-generated audio samples for clarity, naturalness, and technical accuracy. I conduct detailed comparisons of synthetic voices, benchmark speech against human standards, and provide feedback for TTS model improvement. My work ensures consistency, reliability, and improved quality in AI speech output across languages and prompts. • Performed waveform and spectrogram analysis for speech quality • Identified and documented mispronunciations and anomalies in audio output • Assessed phonetic accuracy, pitch, and timing in generated speech • Flagged inconsistencies to improve overall TTS model reliability

2026 - Present

AI Trainer, Generalist/Cybersecurity Domain Expert | Outlier

OtherImageSegmentation
Created annotations, captions, and spatial descriptions for images and videos, transcribed document images, and executed video segmentation tasks. Carried out image generation prompt design, style transfer, object isolation, and background replacement evaluations. Ranked, compared, and assessed multi-modal AI responses and features using detailed rubrics and structured frameworks. • Performed artifact detection, realism checks, and quality assessments for visual data. • Sourced and curated diverse datasets ensuring data quality, compliance, and safety. • Identified edge cases and AI failure scenarios in complex visual reasoning tasks. • Reviewed data reliability, metadata, and diagram structures for annotation accuracy.

Created annotations, captions, and spatial descriptions for images and videos, transcribed document images, and executed video segmentation tasks. Carried out image generation prompt design, style transfer, object isolation, and background replacement evaluations. Ranked, compared, and assessed multi-modal AI responses and features using detailed rubrics and structured frameworks. • Performed artifact detection, realism checks, and quality assessments for visual data. • Sourced and curated diverse datasets ensuring data quality, compliance, and safety. • Identified edge cases and AI failure scenarios in complex visual reasoning tasks. • Reviewed data reliability, metadata, and diagram structures for annotation accuracy.

2026 - Present

AI Trainer, Cybersecurity Expert | Handshake AI Fellowship

OtherText
Evaluated and developed prompts for LLMs across cybersecurity domains, focusing on technical accuracy and depth. Provided structured feedback to enhance model responses in threat analysis, incident response, and vulnerability assessment. Conducted independent research to support prompt development and AI understanding of advanced cybersecurity concepts. • Analyzed LLM outputs for completeness, alignment, and quality in security topics. • Delivered iterative, domain-specific prompt and response reviews for AI model improvement. • Collaborated with engineering and research teams to refine AI-driven cybersecurity solutions. • Contributed expert feedback to reinforce LLM performance in technical and general-knowledge domains.

Evaluated and developed prompts for LLMs across cybersecurity domains, focusing on technical accuracy and depth. Provided structured feedback to enhance model responses in threat analysis, incident response, and vulnerability assessment. Conducted independent research to support prompt development and AI understanding of advanced cybersecurity concepts. • Analyzed LLM outputs for completeness, alignment, and quality in security topics. • Delivered iterative, domain-specific prompt and response reviews for AI model improvement. • Collaborated with engineering and research teams to refine AI-driven cybersecurity solutions. • Contributed expert feedback to reinforce LLM performance in technical and general-knowledge domains.

2025 - Present

Bounding Box Annotation — People & Objects

Internal Proprietary ToolingImageBounding BoxClassification
I completed bounding box annotation tasks for both person-level and general object localization. For person annotation, I sourced large group photographs containing at least ten clearly visible individuals, drew tight bounding boxes around each person with attention to face and upper body coverage, assigned unique contextual background settings for AI image generation, and evaluated the quality of generated portraits against the original subjects — checking for facial feature accuracy, outfit consistency, natural pose variation, and absence of artifacts. For object annotation, I identified target objects from prompt descriptions, drew precise boxes with minimal excess space, and verified edge accuracy using zoom-based quality checks.

I completed bounding box annotation tasks for both person-level and general object localization. For person annotation, I sourced large group photographs containing at least ten clearly visible individuals, drew tight bounding boxes around each person with attention to face and upper body coverage, assigned unique contextual background settings for AI image generation, and evaluated the quality of generated portraits against the original subjects — checking for facial feature accuracy, outfit consistency, natural pose variation, and absence of artifacts. For object annotation, I identified target objects from prompt descriptions, drew precise boxes with minimal excess space, and verified edge accuracy using zoom-based quality checks.

2025

Event Timestamps & Scene Cut Detection

Internal Proprietary ToolingVideoPoint Key PointSegmentation
I reviewed AI-detected scene cuts in video content and verified, corrected, and supplemented them with manually identified segment boundaries. Each cut marker had to be placed on the exact first frame of a new scene or event, requiring frame-by-frame analysis using timeline scrubbing tools. Beyond verifying camera cuts, I further segmented footage based on logical event boundaries — distinct actions or moments occurring within the same camera angle — and applied concise, descriptive labels to each segment. This task demanded sustained focus, precise temporal judgment, and the ability to distinguish meaningful content transitions from irrelevant movement.

I reviewed AI-detected scene cuts in video content and verified, corrected, and supplemented them with manually identified segment boundaries. Each cut marker had to be placed on the exact first frame of a new scene or event, requiring frame-by-frame analysis using timeline scrubbing tools. Beyond verifying camera cuts, I further segmented footage based on logical event boundaries — distinct actions or moments occurring within the same camera angle — and applied concise, descriptive labels to each segment. This task demanded sustained focus, precise temporal judgment, and the ability to distinguish meaningful content transitions from irrelevant movement.

2025

Education

W

Western Governors University

Master of Science, Cybersecurity

Master of Science
2024 - 2025
S

SANS Women's Immersion Academy

Certificate, Cybersecurity

Certificate
2021 - 2022

Work History

H

Handshake AI Fellowship

Cybersecurity Domain Expert - AI Trainer

Land O' Lakes
2025 - Present
S

St. Andrew Post-Acute Rehabilitation

Licensed Physical Therapist Assistant

Tampa, FL
2023 - Present