Hasan Sheikh is a software engineer and AI/LLM code evaluation specialist with hands-on expertise in full-stack development, machine learning, and AI quality assessment. He currently works as an AI Model & LLM Coding Evaluator at DataAnnotation, where he assesses 100+ code-focused LLM responses against multi-criteria rubrics spanning correctness, edge-case handling, readability, efficiency, and instruction-following. He has developed strong pattern recognition for logic errors, specification failures, and algorithmic weaknesses in AI-generated code. His project work includes FactorLab, a full-stack quantitative research platform integrating two ML models (scikit-learn, LightGBM) across six trading strategies, and CampusGuard, an AI-powered platform built in 12 hours that won 1st place at the Deloitte × ServiceNow × University of Canterbury Hackathon (Tech Week NZ 2025). Languages: Python, TypeScript, JavaScript, Java Frameworks & Tools: Next.js, React, PostgreSQL, Supabase, pandas, NumPy, scikit-learn, LightGBM, pytest, Playwright

Hasan Sheikh

Hasan Sheikh is a software engineer and AI/LLM code evaluation specialist with hands-on expertise in full-stack development, machine learning, and AI quality assessment. He currently works as an AI Model & LLM Coding Evaluator at DataAnnotation, where he assesses 100+ code-focused LLM responses against multi-criteria rubrics spanning correctness, edge-case handling, readability, efficiency, and instruction-following. He has developed strong pattern recognition for logic errors, specification failures, and algorithmic weaknesses in AI-generated code. His project work includes FactorLab, a full-stack quantitative research platform integrating two ML models (scikit-learn, LightGBM) across six trading strategies, and CampusGuard, an AI-powered platform built in 12 hours that won 1st place at the Deloitte × ServiceNow × University of Canterbury Hackathon (Tech Week NZ 2025). Languages: Python, TypeScript, JavaScript, Java Frameworks & Tools: Next.js, React, PostgreSQL, Supabase, pandas, NumPy, scikit-learn, LightGBM, pytest, Playwright

Available to hire

Hasan Sheikh is a software engineer and AI/LLM code evaluation specialist with hands-on expertise in full-stack development, machine learning, and AI quality assessment.
He currently works as an AI Model & LLM Coding Evaluator at DataAnnotation, where he assesses 100+ code-focused LLM responses against multi-criteria rubrics spanning correctness, edge-case handling, readability, efficiency, and instruction-following. He has developed strong pattern recognition for logic errors, specification failures, and algorithmic weaknesses in AI-generated code.
His project work includes FactorLab, a full-stack quantitative research platform integrating two ML models (scikit-learn, LightGBM) across six trading strategies, and CampusGuard, an AI-powered platform built in 12 hours that won 1st place at the Deloitte × ServiceNow × University of Canterbury Hackathon (Tech Week NZ 2025).
Languages: Python, TypeScript, JavaScript, Java
Frameworks & Tools: Next.js, React, PostgreSQL, Supabase, pandas, NumPy, scikit-learn, LightGBM, pytest, Playwright

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Work Experience

AI Model & LLM Coding Evaluator at DataAnnotation
January 1, 2026 - Present
Applied rubric-based review across 5+ quality criteria — correctness, edge-case handling, readability, efficiency, and instruction-following — to evaluate 100+ code-focused LLM responses, producing consistent, high-signal feedback for model improvement. Used structured prompt refinement and targeted failure-mode testing to tighten evaluation consistency, reducing scoring variance across assessments.
Fast Food Team Member at KFC
November 1, 2025 - February 1, 2026
Engaged with customers, took orders, and ensured smooth operation of the fast-food outlet by adhering to quality and customer service standards.
Fast Food Team Member at McDonald's
August 1, 2023 - September 1, 2024
Contributed to team efforts in a fast-paced environment, maintaining service quality and customer satisfaction during peak hours.

Education

Bachelor of Computer Science, Minor in Statistics at University of Canterbury
January 1, 2023 - November 1, 2027

Qualifications

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