Chinasa Okonkwo

Key Skills

Software

AWS SageMaker

Telus

Top Subject Matter

Finance

AI Agent Governance

Recommendation Systems

Top Data Types

Text

Document

Image

Top Task Types

Fine-tuning

Data Collection

Segmentation

Text Generation

Text Summarization

Evaluation/Rating

Freelancer Overview

Data Scientist / GenAI Engineer. Brings 13+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include AWS SageMaker. Education includes Master of Science, New York Institute of Technology (2024) and Postgraduate Diploma, The University of Texas at Austin (2023). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning.

Labeling Experience

Data Scientist / GenAI Engineer

Aws SagemakerTextFine Tuning

I co-designed and engineered AI products involving large language models for food intelligence and agent governance applications. My responsibilities included building personalized recommendation engines supported by menu and dietary classification pipelines and fine-tuning large language models (LLMs). LLM fine-tuning required creation and curation of specialized text datasets and performing evaluation activities for model optimization purposes. • Built and maintained custom datasets for LLM fine-tuning (GPT-3.5/4o, BERT, Llama 2) • Performed iterative evaluation and prompt engineering as part of the supervised fine-tuning workflow • Classified and structured textual and menu-based data for use in generative AI pipelines • Implemented regular evaluation of model outputs to ensure consistent performance and accuracy

I co-designed and engineered AI products involving large language models for food intelligence and agent governance applications. My responsibilities included building personalized recommendation engines supported by menu and dietary classification pipelines and fine-tuning large language models (LLMs). LLM fine-tuning required creation and curation of specialized text datasets and performing evaluation activities for model optimization purposes. • Built and maintained custom datasets for LLM fine-tuning (GPT-3.5/4o, BERT, Llama 2) • Performed iterative evaluation and prompt engineering as part of the supervised fine-tuning workflow • Classified and structured textual and menu-based data for use in generative AI pipelines • Implemented regular evaluation of model outputs to ensure consistent performance and accuracy

2024 - 2024

Education

Work History