Jeremiah A.

Key Skills

Software

Remotasks

Other

Top Subject Matter

LLM training data evaluation and technical code generation quality assurance.

Technical implementation supporting AI-adjacent operations via web/API correctness work.

Legal Services & Contract Review

Top Data Types

Text

Document

Top Task Types

Question Answering

Text Generation

Transcription

Computer Programming/Coding

Prompt + Response Writing (SFT)

Classification

Freelancer Overview

AI Technical Contributor & Analyst in Contract Review, Compliance, and Legal Research. Brings 11+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Remotasks and Other. Education includes Bachelor of Laws, University of Embu and Certificate, Citizen College (2023). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Evaluation, Rating, and Computer Programming.

Labeling Experience

Web Developer (Technical Focus) | Independent Projects / Citizen College (2023 – Present)

Other

You built and deployed custom-coded responsive websites using HTML, CSS, and JavaScript as part of independent projects. You also managed end-to-end digital operations for clients, including API integrations and backend troubleshooting, to support reliable technical delivery. While this was not traditional AI dataset labeling, the work involved structured technical implementation and code correctness practices. • Developed and optimized front-end code for performance and SEO outcomes. • Performed backend and integration troubleshooting to ensure system correctness. • Implemented internal tracking systems to streamline reporting and project management. • Managed client DNS and API configuration tasks for operational reliability.

2023 - Present

AI Technical Contributor & Analyst | Remotasks / Appen / Atlas (2016 – Present)

Remotasks

You evaluated and refined code-generation datasets for Large Language Models (LLMs), focusing on technical accuracy of Python and JavaScript outputs. You managed high-priority data pipelines with a 98%+ accuracy rating to meet international benchmark expectations. You identified edge cases and provided structured feedback to improve model reliability for technical queries. • Reviewed and assessed generated code for correctness and compliance with expected technical behavior. • Refined dataset items to improve dataset quality and downstream model performance. • Logged and communicated edge-case findings and troubleshooting guidance. • Ensured consistent evaluation quality across ongoing pipeline work.

2016 - Present

Education

Work History