Steve S.

Key Skills

Software

Other

Label Studio

Data Annotation Tech

LabelImg

Top Subject Matter

Data preprocessing for AI/ML training datasets

Mathematical reasoning dataset creation/annotation

AI training content creation and review-oriented technical writing

Top Data Types

Text

Document

Computer Code Programming

Top Task Types

Text Generation

Classification

Question Answering

Evaluation/Rating

Computer Programming/Coding

Data Collection

Prompt + Response Writing (SFT)

Text Summarization

RLHF

Entity (NER) Classification

Freelancer Overview

Python Automation & Data Processing Scripts (Personal Project). Core strengths include Other. Education includes Bachelor of Science, Maseno University and Kenya Certificate of Secondary Education, N/A. AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Computer Programming, Coding, and Evaluation.

Labeling Experience

Technical Explainer Content Creation (Personal Project)

OtherTextText Generation

You produced technical explainer content covering computer networking, cybersecurity, and programming concepts to practice writing accurate, clear material for AI training content review. While not described as labeling in a paid production pipeline, this content creation supports dataset generation and review tasks used in AI tutoring and training workflows. Your output aligns with the need for structured, high-quality instructional text. • Wrote technical explainers with a focus on accuracy and clarity. • Covered STEM and computing topics relevant to AI training content. • Practiced documentation style suitable for training and review contexts. • Emphasized structured presentation of technical knowledge.

2025 - Present

Mathematical Reasoning Dataset Curation (Personal Project)

OtherText

You curated and structured a mathematical reasoning dataset with annotated step-by-step solutions formatted for potential AI math-reasoning model training. Your annotation work emphasizes correct notation, logical solution flow, and clear explanation suitable for supervised training and quality evaluation. This constitutes direct creation of labeled training content for LLM or reasoning models. • Compiled algebra and calculus problems into a structured dataset. • Added step-by-step solution annotations with clear reasoning. • Formatted content to support prospective AI math-reasoning training. • Focused on logical sequence, correct notation, and explanation clarity.

2025 - Present

Python Automation & Data Processing Scripts (Personal Project)

Other

You built Python scripts to automate file organization, parse structured text files, and extract data fields for downstream machine learning workflows. These activities support data preparation and annotation pipelines by ensuring consistent formatting and extraction of labeled inputs. Your work demonstrates a labeling-adjacent focus on preprocessing, structured data handling, and automation readiness for AI training tasks. • Automated organization of datasets to maintain labeling-ready directory structures. • Parsed structured text files to extract fields required for consistent annotations. • Demonstrated pipeline thinking applicable to labeling and preprocessing tasks. • Implemented scripting-based efficiencies for repeatable data preparation steps.

2025 - Present

Education

Work History