Eric L.

Key Skills

Software

Other

Top Subject Matter

Chinese language AI evaluation

LLM response evaluation

and AI output QA

Top Data Types

Text

Document

Image

Top Task Types

Computer Programming/Coding

Bounding Box

Polygon

Segmentation

Classification

Entity (NER) Classification

Point/Key Point

Polyline

Cuboid

Object Detection

Text Generation

Question Answering

Text Summarization

Transcription

Data Collection

Function Calling

Evaluation/Rating

Freelancer Overview

AI Evaluation & Applied AI Projects (AI response evaluation and labeling/QA feedback), 2022 - Present. Brings 16+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other, Internal, and Proprietary Tooling. Education includes Artificial Intelligence Trainer Level 3 Certificate, N/A. AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Evaluation & Applied AI Projects (AI response evaluation and labeling/QA feedback), 2022 - Present

OtherText

Provided AI response evaluation for multiple Chinese-language and content-generation scenarios, focusing on correctness, usefulness, fluency, and task compliance. Reviewed semantic accuracy, readability, cultural context, and annotation consistency for Chinese outputs, and compared model behavior against expected instruction-following. Authored structured QA feedback capturing edge cases, failure patterns, user experience issues, and rubric ideas for scoring consistency. • Evaluated AI-assisted speaking assessment outputs and pronunciation/scoring feedback quality • Validated Chinese reading and classical text related outputs for semantic nuance and rare-character support • Checked template-based poster/content generation results for output quality and compliance • Produced rubric-based and edge-case documentation to guide further AI training/evaluation

2022 - Present

Senior iOS Engineer / AI Application Developer (AI evaluation-supporting QA in product workflows), 2011 - Present

Text

Supported AI application development with extensive practical judgment around assessing AI answers in user-facing product contexts. Coordinated engineering quality and requirements that rely on evaluation rigor, test planning, and feedback loops for correctness and user experience. While primarily a software leadership role, his AI-relevant evaluation contributions included reviewing technical AI responses and ensuring them met product expectations. • Assisted in evaluating AI-driven developer/workflow outputs for practical correctness • Led cross-functional coordination to align product requirements with evaluation criteria • Leveraged long-term technical QA judgment to improve AI answer reliability • Participated in numerous AI-relevant software projects emphasizing evaluation and quality review

2011 - Present

Education

Work History