Tochukwu C.

Key Skills

Software

Other

Top Subject Matter

LLM Evaluation and Prompt Engineering

Genealogical Data Annotation

Video Data Labeling

Top Data Types

Video

Computer Code Programming

Document

Top Task Types

Entity (NER) Classification

Classification

Freelancer Overview

LLM Output Evaluator, Turing (NVIDIA Project). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Senior Secondary School Certificate, Comprehensive Secondary School Oruku (2021) and Bachelor of Science, Brigham Young University (Online). AI-training focus includes data types such as Text, Document, and Video and labeling workflows including Evaluation, Rating, and Entity (NER) Classification.

Labeling Experience

Data/Video Labeling Specialist, Altlas Capture

OtherVideoClassification

At Altlas Capture, I work on labeling and classifying data types in video datasets. The tasks include accurately assigning categories to sequences of video based on predefined criteria and project specifications. This requires consistent attention to detail and adherence to annotation protocols. • Classify and label video segments according to guidelines. • Use specialized annotation tools to maintain data integrity. • Review and refine existing annotations for consistency. • Collaborate with team members to resolve annotation challenges.

2025 - Present

LLM Output Evaluator, Turing (NVIDIA Project)

Text

During my work with Turing on the NVIDIA Project, I was responsible for evaluating the outputs of large language models (LLMs). My duties included designing prompts to rigorously test instructional compliance and reasoning, as well as systematically comparing model responses against industry benchmarks. This required keen attention to detail and the ability to document rationales to support evaluation outcomes. • Designed and tested multi-turn LLM prompts. • Evaluated LLM outputs for quality, accuracy, and structure. • Compared and ranked model responses to determine overall output quality. • Created structured explanations and maintained traceability of scoring logic.

2025 - 2025

Volunteer Data Annotation & Verification, FamilySearch

OtherDocumentEntity (NER) Classification

As a data annotation and verification volunteer for FamilySearch, I indexed large volumes of genealogical records. This role demanded precise identification and recording of names, relationships, and demographic details across diverse document types. I consistently upheld high accuracy standards by following structured review and correction processes. • Indexed and verified over 600,000 records containing personal, relational, and temporal data. • Estimated and annotated dates of birth using historical context. • Performed quality checks and error corrections to maintain accuracy rates above 98%. • Applied strict review guidelines to metadata and entity extraction tasks.

2024 - 2025

Education

Work History