Key Skills

Software

Scale AI

Labelbox

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Text

Image

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Computer Code Programming

Top Label Types

Prompt Response Writing SFT

Evaluation Rating

Freelancer Overview

I am a highly skilled DevOps and DevSecOps Engineer with a strong background in managing and automating complex data pipelines, infrastructure, and security processes for large-scale applications. My experience includes orchestrating containerized environments, implementing CI/CD workflows, and deploying monitoring solutions that ensure data quality and integrity—key aspects for reliable AI training data and annotation workflows. I have worked extensively with tools like Kubernetes, Docker, Jenkins, Ansible, Python, Prometheus, and Grafana, and have hands-on experience with cloud platforms such as AWS and GCP. My roles have required meticulous management of data flows, secure handling of sensitive information, and collaboration with cross-functional teams to deliver robust solutions for real-time data acquisition and processing. I am passionate about leveraging automation and best practices to support high-quality data labeling, annotation, and AI-driven projects across diverse domains.

Labeling Experience

AI Data Annotator and LLM Alignment and Eval

LabelboxComputer Code ProgrammingEvaluation RatingPrompt Response Writing SFT

Contributed to AI alignment projects focused on improving large language model performance through structured prompt-response writing and evaluation. Generated high-quality supervised fine-tuning (SFT) data, assessed model outputs for reasoning, factual accuracy, clarity, and policy compliance, and provided detailed feedback to enhance model reliability and safety. Applied strict annotation guidelines and quality standards to ensure consistency and scalability across datasets.

Contributed to AI alignment projects focused on improving large language model performance through structured prompt-response writing and evaluation. Generated high-quality supervised fine-tuning (SFT) data, assessed model outputs for reasoning, factual accuracy, clarity, and policy compliance, and provided detailed feedback to enhance model reliability and safety. Applied strict annotation guidelines and quality standards to ensure consistency and scalability across datasets.

2025

Education

Work History