Key Skills

Software

Data Annotation Tech

Telus

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Freelancer Overview

I am an experienced AI Model Trainer and Data Annotator with a strong background in software engineering and over two years specializing in optimizing large language models (LLMs) through RLHF and multimodal annotation. My expertise spans data sanitization, metacognitive feedback, and detailed chain-of-thought reporting, particularly for complex linguistic structures, such as Bantu languages. I have worked on high-stakes data curation and model evaluation projects across domains including computer vision and NLP, collaborating with ML engineers to refine taxonomies, reduce model hallucinations, and enhance safety guardrails. Proficient in Python, Google Cloud, and technical documentation, I am committed to delivering high-quality, bias-free datasets and actionable insights that drive model robustness and accuracy.

Labeling Experience

Technical AI Evaluator (Contract)

TelusTextEvaluation Rating

Collaborated with Machine Learning Engineers to refine labeling taxonomies and align annotation outputs with key model performance KPIs. Performed rigorous evaluations and feedback cycles for LLMs, emphasizing reduction of hallucinations in logical reasoning tasks. Authored technical documentation and SOPs to standardize annotation and quality across teams. • Evaluated alternative data-weighting perspectives supporting project pivots. • Conducted model performance assessments to improve logical output integrity. • Wrote visual reports using productivity toolkits to communicate annotation results. • Standardized processes for high-quality annotation output.

Collaborated with Machine Learning Engineers to refine labeling taxonomies and align annotation outputs with key model performance KPIs. Performed rigorous evaluations and feedback cycles for LLMs, emphasizing reduction of hallucinations in logical reasoning tasks. Authored technical documentation and SOPs to standardize annotation and quality across teams. • Evaluated alternative data-weighting perspectives supporting project pivots. • Conducted model performance assessments to improve logical output integrity. • Wrote visual reports using productivity toolkits to communicate annotation results. • Standardized processes for high-quality annotation output.

2025 - 2025

Expert AI Trainer and Multimodal Annotator

Data Annotation TechAudioAudio Recording

Managed a broad array of multimodal annotation tasks including high-quality audio recording, image annotation, and dataset cleansing for computer vision and LLM datasets. Authored detailed 'chain-of-thought' reports pinpointing failure modes and provided actionable metacognitive feedback for ML Engineers. Ensured strict compliance with privacy and accuracy protocols in dataset curation for AI and code-generation models. • Deep-cleansed large-scale datasets to eliminate bias and adhere to guidelines. • Annotated images and audio for computer vision models and LLM optimization. • Delivered high-stakes data curation and feedback to strengthen model reasoning. • Processed and quality-checked datasets across annotation tasks.

Managed a broad array of multimodal annotation tasks including high-quality audio recording, image annotation, and dataset cleansing for computer vision and LLM datasets. Authored detailed 'chain-of-thought' reports pinpointing failure modes and provided actionable metacognitive feedback for ML Engineers. Ensured strict compliance with privacy and accuracy protocols in dataset curation for AI and code-generation models. • Deep-cleansed large-scale datasets to eliminate bias and adhere to guidelines. • Annotated images and audio for computer vision models and LLM optimization. • Delivered high-stakes data curation and feedback to strengthen model reasoning. • Processed and quality-checked datasets across annotation tasks.

2025 - 2025

AI Model Trainer/Data Annotator

TextRLHF

Trained and verified LLMs through reinforcement learning from human feedback to test and improve model reasoning and conversational logic. Identified and documented high-harm hallucinations, constructing robust safety guardrails and alignment strategies for AI systems. Developed and implemented edge-case prompt engineering scenarios for model robustness testing. • Performed RLHF and logic verification on large language models. • Created safety mechanisms to mitigate model hallucinations and user interface risks. • Authored test protocols for scenario-based anomaly and edge case handling. • Systematically improved model robustness through structured evaluation.

Trained and verified LLMs through reinforcement learning from human feedback to test and improve model reasoning and conversational logic. Identified and documented high-harm hallucinations, constructing robust safety guardrails and alignment strategies for AI systems. Developed and implemented edge-case prompt engineering scenarios for model robustness testing. • Performed RLHF and logic verification on large language models. • Created safety mechanisms to mitigate model hallucinations and user interface risks. • Authored test protocols for scenario-based anomaly and edge case handling. • Systematically improved model robustness through structured evaluation.

2024 - 2025

Education

Work History