Dennis Ochieng

Key Skills

Software

Appen

CloudFactory

OneForma

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Video

Top Label Types

Audio Recording

Data Collection

Fine Tuning

Freelancer Overview

I have extensive experience in data labeling and AI training data workflows, particularly in supporting the development of large-scale machine learning models. At Invisible Technologies, I’ve contributed as an AI Data Trainer by curating, annotating, and quality-checking training datasets with a focus on precision, consistency, and scalability. My work has involved both structured and unstructured data, including text classification, entity recognition, intent tagging, and image annotation, using proprietary tools and platforms. I’ve collaborated with cross-functional teams to meet strict accuracy standards, implement feedback loops, and iterate quickly on evolving task guidelines, ensuring model outputs align with client expectations. What sets me apart is a deep understanding of the impact high-quality labeled data has on model performance, combined with a meticulous attention to detail and a process-driven mindset. I bring a strong ability to interpret nuanced instructions, adapt to domain-specific requirements, and balance throughput with quality. My experience working on mission-critical datasets for enterprise-level AI systems, along with a commitment to operational excellence, has allowed me to deliver reliable results under tight deadlines.

Labeling Experience

Audio Data Labeling

AppenAudioSegmentationClassification

I have hands-on experience in audio data labeling, specializing in tasks such as transcription, speaker identification, intent recognition, and sound classification. At Invisible Technologies, I contributed to AI training projects for clients like OpenAI and Gemini (Google), where I labeled and curated high-quality audio datasets to train and fine-tune machine learning models. My responsibilities included segmenting audio clips, ensuring accurate transcriptions, tagging non-verbal cues, and annotating contextual information, all while adhering to strict quality and consistency standards. This work required acute attention to detail, strong linguistic skills, and the ability to differentiate between accents, emotions, and background noise. I consistently met productivity and accuracy targets in a fast-paced environment, supporting the development of advanced voice assistants, transcription tools, and conversational AI systems.

I have hands-on experience in audio data labeling, specializing in tasks such as transcription, speaker identification, intent recognition, and sound classification. At Invisible Technologies, I contributed to AI training projects for clients like OpenAI and Gemini (Google), where I labeled and curated high-quality audio datasets to train and fine-tune machine learning models. My responsibilities included segmenting audio clips, ensuring accurate transcriptions, tagging non-verbal cues, and annotating contextual information, all while adhering to strict quality and consistency standards. This work required acute attention to detail, strong linguistic skills, and the ability to differentiate between accents, emotions, and background noise. I consistently met productivity and accuracy targets in a fast-paced environment, supporting the development of advanced voice assistants, transcription tools, and conversational AI systems.

2019 - 2021

Education

Work History