Nnamani S.

Key Skills

Software

Other

Top Subject Matter

Conversational AI for appointment scheduling (voice-driven workflow automation)

Supervised ML predictive modeling (classification)

Workflow automation for candidate onboarding data processing

Top Data Types

Audio

Text

Document

Image

Top Task Types

Function Calling

Fine-tuning

Data Collection

Classification

Freelancer Overview

AI Systems & Automation Engineer — voice AI appointment scheduling orchestration. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include n8n, Other, and Make.com. Education includes Bachelor of Engineering, Nnamdi Azikiwe University (2015). AI-training focus includes data types such as Audio, Text, and Document and labeling workflows including Function Calling, Fine-tuning, and Data Collection.

Labeling Experience

Automation & CRM Systems Engineer — event-driven onboarding workflow orchestration

DocumentData Collection

Designed automated onboarding workflows that process form submissions and conditionally update candidate status. The work centered on pipeline orchestration, event-driven processing, and CRM synchronization to maintain real-time visibility. While not human annotation, it involved building structured data processing steps for downstream evaluation. • Integrated Zoho Forms with Make.com and Zoho CRM for onboarding pipeline stages • Created event-driven workflows to trigger evaluation steps and update statuses • Implemented recurring notifications to reduce onboarding drop-offs • Automated onboarding lifecycle management to reduce manual intervention

2025 - 2026

AI Systems & Automation Engineer — voice AI appointment scheduling orchestration

AudioFunction Calling

Engineered an AI-driven conversational appointment booking workflow combining voice interactions and automated decisioning. The work focused on orchestrating call flows, conditional routing, and booking actions rather than manual data annotation. This supported end-to-end real-time scheduling using external tools and cloud storage. • Implemented voice AI appointment booking via a conversational interface • Built event-driven workflows for call routing and booking decisions • Integrated Google Calendar for availability checks and scheduling updates • Stored user data, logs, and appointment records in Airtable

2025 - 2026

Machine Learning Intern — predictive modeling and classification

OtherTextFine-tuning

Worked on machine learning projects involving predictive modeling and classification techniques. The role emphasized building decision-tree-based predictive models for anticipating customer behavior. This reflects AI training and modeling work using structured datasets rather than data labeling tools. • Implemented predictive modeling models using classification workflows • Used decision tree methods to anticipate customer behavior • Collaborated on multiple ML projects with iterative experimentation • Applied standard ML approaches for model building and evaluation

2020

Education

Work History