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Prabhu J

Prabhu J

AI Trainer — LLM Evaluation & Data Annotation | Apple

India flagHyderabad, India
$20.00/hrExpertInternal Proprietary Tooling

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

Multilingual LLM training
AI content evaluation
Rlhf Domain Expertise

Top Data Types

AudioAudio
ImageImage
VideoVideo

Top Task Types

Bounding BoxBounding Box
SegmentationSegmentation
ClassificationClassification
Object DetectionObject Detection
Text SummarizationText Summarization
RLHFRLHF
Fine-tuningFine-tuning
Red TeamingRed Teaming
TranscriptionTranscription
Evaluation/RatingEvaluation/Rating
Data CollectionData Collection
Computer Programming/CodingComputer Programming/Coding

Freelancer Overview

AI Trainer — LLM Evaluation & Data Annotation | Apple. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Engineering, SDES, Hyderabad (2017). AI-training focus includes data types such as Text and Audio and labeling workflows including Evaluation and Rating.

ExpertEnglishTeluguHindi

Labeling Experience

AI Trainer — Speech and Audio Evaluation | Apple

Audio
In my role at Apple, I was involved in the evaluation of AI-generated speech and audio outputs for Siri's voice interface across multiple languages. My responsibilities included assessing linguistic accuracy, naturalness, and fluency of audio content, as well as annotating performance issues and documenting calibration feedback. I collaborated with distributed teams to ensure consistent audio quality standards and zero SLA breaches over six consecutive years. • Assessed AI-generated audio/speech for accuracy, naturalness, and regional appropriateness. • Annotated and rated audio outputs utilizing structured quality compliance rubrics. • Integrated quality assurance feedback and participated in rubric calibration sessions. • Maintained compliance with stringent quality guidelines for high-volume audio datasets.

In my role at Apple, I was involved in the evaluation of AI-generated speech and audio outputs for Siri's voice interface across multiple languages. My responsibilities included assessing linguistic accuracy, naturalness, and fluency of audio content, as well as annotating performance issues and documenting calibration feedback. I collaborated with distributed teams to ensure consistent audio quality standards and zero SLA breaches over six consecutive years. • Assessed AI-generated audio/speech for accuracy, naturalness, and regional appropriateness. • Annotated and rated audio outputs utilizing structured quality compliance rubrics. • Integrated quality assurance feedback and participated in rubric calibration sessions. • Maintained compliance with stringent quality guidelines for high-volume audio datasets.

2019 - Present

AI Trainer — LLM Evaluation & Data Annotation | Apple

Text
As an AI Trainer specializing in LLM Evaluation and Data Annotation at Apple, I performed rigorous evaluation and labeling of AI-generated text and conversational content across 10+ language tracks including Telugu, Hindi, and English. My work involved structured rubric application for accuracy, tone, and safety assessment, as well as documentation of hallucinations and reasoning failures. I generated high-quality training data, performed pairwise preference ranking for RLHF, and contributed to rubric design and error trace documentation. • Evaluated and rated thousands of LLM outputs daily for factual consistency and cultural appropriateness. • Applied structured rubrics to label text, conversational, and multilingual audio outputs with exceptional accuracy. • Performed pairwise comparisons and generated RLHF/preference datasets for further model improvement. • Detected and meticulously documented hallucinations, inconsistencies, and failure modes.

As an AI Trainer specializing in LLM Evaluation and Data Annotation at Apple, I performed rigorous evaluation and labeling of AI-generated text and conversational content across 10+ language tracks including Telugu, Hindi, and English. My work involved structured rubric application for accuracy, tone, and safety assessment, as well as documentation of hallucinations and reasoning failures. I generated high-quality training data, performed pairwise preference ranking for RLHF, and contributed to rubric design and error trace documentation. • Evaluated and rated thousands of LLM outputs daily for factual consistency and cultural appropriateness. • Applied structured rubrics to label text, conversational, and multilingual audio outputs with exceptional accuracy. • Performed pairwise comparisons and generated RLHF/preference datasets for further model improvement. • Detected and meticulously documented hallucinations, inconsistencies, and failure modes.

2019 - Present

Education

S

SDES, Hyderabad

Bachelor of Engineering, Electronics and Communication Engineering

Bachelor of Engineering
2017 - 2017

Work History

A

Apple

Grading Specialist 2

Hyderabad
2019 - Present