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Nikita W.

Nikita W.

Software Engineering Challenge Designer · AfterQuery (Applied)

Kenya flagNairobi, Kenya

Key Skills

Software

Data Annotation TechData Annotation Tech
Scale AIScale AI
CloudFactoryCloudFactory
ClickworkerClickworker

Top Subject Matter

AI-generated code evaluation and software engineering challenge design
Peer code review and annotation for AI training and RLHF workflows
Open-source code review and annotation for AI training and evaluation

Top Data Types

Computer Code ProgrammingComputer Code Programming
ImageImage
DocumentDocument

Top Task Types

PolygonPolygon
Bounding BoxBounding Box
ClassificationClassification
SegmentationSegmentation
Entity (NER) ClassificationEntity (NER) Classification

Freelancer Overview

Software Engineering Challenge Designer · AfterQuery (Applied). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, University of Cape Town (2025). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Computer Programming, Coding, and Evaluation.

Labeling Experience

Open Source Code Reviewer · GitHub

I participated as an open-source code reviewer on GitHub, specializing in evaluating and annotating pull requests in Python and Java repositories. My role included detecting edge cases, suggesting improvements, and documenting rationale in the annotation process. This experience mirrored professional annotation standards in code review, relevant to AI evaluation and data labeling workflows. • Evaluated open-source code contributions for quality and safety. • Used structured review rubrics to label model-generated code changes. • Identified edge cases and flagged unsafe or inefficient logic. • Provided comprehensive written feedback for each annotation.

2023 - Present

Software Engineering Challenge Designer · AfterQuery (Applied)

In this role, I designed high-quality coding challenges to test and benchmark AI models and their code generation abilities. I evaluated and annotated AI-generated model responses for algorithm design, debugging, system architecture, and API design using technical feedback. I also created adversarial scenarios to identify and document weaknesses in AI code reasoning and capabilities. • Crafted and reviewed coding challenges and edge-case prompts. • Provided feedback on AI-generated code for correctness and best practices. • Focused on error detection and technical code evaluation. • Worked with Python, Java, and Rust in AI model assessment.

2025 - 2025

Code Quality Reviewer & Annotator · Personal & Academic Projects

I reviewed and annotated algorithm implementations across Python, Java, and Rust for data labeling and AI evaluation. The work involved identifying and documenting logic errors, bugs, and inefficiencies in code for structured feedback. Detailed written rubrics were applied, modeling best practices from RLHF annotation workflows. • Annotated peer code for technical correctness and clarity. • Focused on bug detection and detailed feedback documentation. • Produced clear evaluation rationales to guide model improvement. • Worked extensively in Python, Java, and Rust environments.

2023 - 2025

Education

U

University of Cape Town

Bachelor of Science, Computer Science

Bachelor of Science
2021 - 2025

Work History

G

GitHub

Open Source Contributor

Cape Town
2023 - Present