Stanley O.

Key Skills

Software

Don't disclose

Top Subject Matter

LLM evaluation and AI model assessment

AI training/validation workflows and grading/annotation

AI training infrastructure and software evaluation pipelines

Top Data Types

Text

Top Task Types

Text Generation

Freelancer Overview

Project: AI Evaluation & Optimization Platform (2023 - N/A). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Doctor of Philosophy, University of Debrecen (2026) and Master of Science, University of Debrecen (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Text Generation.

Labeling Experience

Senior Full-Stack / AI Engineer at Handshake AI (2025 - Present)

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Performed AI model evaluation work by reviewing outputs and contributing to prompt optimization and reliability improvements for real-time AI systems. Supported structured evaluation workflows and debugging processes related to grading and annotation pipelines. Collaborated on data-intensive systems requiring analytical review and structured feedback to improve model quality. • Evaluated AI model outputs for quality and reliability • Contributed to prompt optimization initiatives • Collaborated on structured feedback processes for evaluation • Supported distributed processing for evaluation workflows

2025 - Present

Full-Stack Software Engineer at Outlier AI (2024 - Present)

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Built internal evaluation tools and dashboards to support AI model assessment workflows. Developed scalable backend services and data pipelines used for grading and annotation systems, including caching and performance optimization. Completed evaluation tasks involving structured analysis, technical reasoning, and debugging to support AI training and validation projects. • Developed evaluation dashboards and internal tools • Built grading/annotation data pipelines • Implemented caching and optimized data processing • Supported AI training/validation with high technical accuracy

2024 - Present

Software Engineer at Scale AI (2023 - 2024)

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Engineered backend services and processing pipelines for large-scale AI data systems used in training and evaluation contexts. Optimized distributed processing workflows to improve system efficiency for AI training infrastructure and model evaluation initiatives. Collaborated with technical teams on debugging, system optimization, and infrastructure reliability supporting AI data handling. • Supported AI model training infrastructure and evaluation initiatives • Optimized distributed processing workflows • Built processing pipelines for AI data systems • Assisted with debugging and reliability improvements

2023 - 2024

Machine Learning Engineer at IBM (2022 - 2023)

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Developed and deployed NLP and machine learning applications that included building APIs for model serving and real-time processing. Improved reliability and performance of AI pipelines through testing and optimization for structured datasets and analytics workflows. Supported cloud-based deployment systems for production AI behavior, enabling iterative validation of NLP outputs. • Built NLP/ML applications for production environments • Implemented APIs for model serving and real-time processing • Improved reliability/performance via testing and optimization • Worked with structured datasets and analytics workflows

2022 - 2023

Project: AI Evaluation & Optimization Platform (2023 - N/A)

Don't discloseTextText Generation

Created structured workflows for annotation, validation, and prompt evaluation to improve the reliability and consistency of model-generated outputs. Developed evaluation tools focused on assessing AI model responses and increasing output quality. Implemented iterative improvements through validation checks and structured prompt assessment. • Developed evaluation tools for AI responses • Built annotation/validation/prompt-evaluation workflows • Improved reliability and consistency of outputs • Used structured validation to drive prompt evaluation

2023

Education

Work History