Jonathan O.

Key Skills

Software

Don't disclose

Other

Internal/Proprietary Tooling

Top Subject Matter

LLM fine-tuning for domain-specific memory extraction

RAG and personalized memory agents

AI/ML-adjacent software engineering education (Python/JavaScript mentoring)

Top Data Types

Audio

Image

Text

Top Task Types

Fine-tuning

Entity (NER) Classification

Text Generation

Question Answering

Text Summarization

Function Calling

Prompt + Response Writing (SFT)

Data Collection

RLHF

Classification

Bounding Box

Freelancer Overview

Lead AI Engineer | ELZAI (Memora). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose and Other. Education includes Advanced Diploma in Software Engineering, Aptech Computer Education (2023) and National Diploma in Computer Science, Federal College of Agriculture, Enugu (2019). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Fine-tuning, Computer Programming, and Coding.

Labeling Experience

Lead AI Engineer | ELZAI (Memora)

Don't discloseFine-tuning

Led development of a memory-focused AI framework that performs LLM-driven memory extraction for agent personalization and semantic search. Fine-tuned open-source LLMs for domain-specific memory extraction and improved recall precision on long-horizon conversations. Integrated graph and vector database workflows to support temporal recall and cross-agent memory sharing. • Configured pipelines for extracting structured memory signals from conversational context • Trained/fine-tuned LLaMA 3 and Mixtral for memory extraction objectives • Evaluated semantic search and recall performance for long-horizon chats • Supported multi-tenant memory versioning and temporal retrieval across agents

2024 - Present

Assistant Faculty | Aptech Computer Education

Other

Provided instruction and hands-on mentoring in software engineering fundamentals with a focus on Python and JavaScript. Supported learners through practical coding exercises that build capability for implementing AI-related software components. Assisted students in applying development concepts during guided sessions. • Delivered coding-focused teaching for Python and JavaScript fundamentals • Mentored learners with hands-on exercises and review • Supported understanding of programming workflows relevant to building AI applications • Reinforced implementation practices through guided practice sessions

2022 - 2022

Education

Work History