Salwa Philips

Key Skills

Software

iMerit

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Text

Video

Top Label Types

Action Recognition

Audio Recording

Classification

Data Collection

Diagnosis

Evaluation Rating

Object Detection

Segmentation

Text Generation

Text Summarization

Transcription

Translation Localization

Freelancer Overview

I am a detail-oriented professional with hands-on experience in data annotation, transcription, and quality control for AI and language training data. My background includes transcribing and annotating student responses for Pearson, where I produced high-quality, word-for-word transcripts to support speech recognition system improvements in the education domain. I have a strong command of data review, editing, and compliance, ensuring accuracy and consistency across diverse datasets. My technical toolkit includes advanced Excel, Google Workspace, Jira, and collaboration platforms like Confluence and SharePoint. I am skilled at working with cross-functional teams to troubleshoot issues, implement workflow optimizations, and deliver precise, actionable feedback on data quality. With a commitment to upholding high standards and deadlines, I am passionate about supporting AI and machine learning projects that rely on clean, well-labeled data.

Labeling Experience

AI Annotator

ImeritTextEvaluation Rating

As an AI Annotator at iMerit, I evaluated and quality-checked large language model (LLM) outputs across text, image caption, video description, and multimodal prompts for accuracy and appropriateness. I identified and resolved errors, biases, and ambiguities by applying domain expertise and logical reasoning, escalating edge cases as needed. I delivered consistent feedback and scoring by tagging outputs and collaborating with project teams to meet accuracy and turnaround goals. • Evaluated LLM-generated outputs for accuracy, coherence, and safety. • Applied expertise to resolve ambiguities, biases, and errors. • Tagged, documented, and scored outputs in collaboration with quality leads. • Contributed to improving evaluation standards and project outcomes.

As an AI Annotator at iMerit, I evaluated and quality-checked large language model (LLM) outputs across text, image caption, video description, and multimodal prompts for accuracy and appropriateness. I identified and resolved errors, biases, and ambiguities by applying domain expertise and logical reasoning, escalating edge cases as needed. I delivered consistent feedback and scoring by tagging outputs and collaborating with project teams to meet accuracy and turnaround goals. • Evaluated LLM-generated outputs for accuracy, coherence, and safety. • Applied expertise to resolve ambiguities, biases, and errors. • Tagged, documented, and scored outputs in collaboration with quality leads. • Contributed to improving evaluation standards and project outcomes.

2026

Data Annotator

Internal Proprietary ToolingTextTranscription

As a Data Annotator with Pearson, I transcribed students’ spoken utterances word for word using specific text annotation guidelines. I produced high-quality transcripts for recorded English language proficiency test responses. I ensured each transcript was accurate and detailed to support improvements in speech recognition testing systems. • Generated word-for-word transcripts for ESL student responses. • Maintained attention to detail for high accuracy and quality. • Edited and reviewed audio data to ensure precise annotation. • Supported development of speech recognition evaluation tools.

As a Data Annotator with Pearson, I transcribed students’ spoken utterances word for word using specific text annotation guidelines. I produced high-quality transcripts for recorded English language proficiency test responses. I ensured each transcript was accurate and detailed to support improvements in speech recognition testing systems. • Generated word-for-word transcripts for ESL student responses. • Maintained attention to detail for high accuracy and quality. • Edited and reviewed audio data to ensure precise annotation. • Supported development of speech recognition evaluation tools.

2020 - 2021

Education

Work History