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Freelancer Overview

I bring hands-on experience in system validation, diagnostics, and quality assurance testing across advanced vehicle platforms, which directly translates into expertise with structured data labeling, trace analysis, and logging workflows required for AI training data. At Volkswagen Group of America's Innovation Engineering Center, I documented and analyzed over 300 system-level defects, leveraging tools like ODIS Engineering, Idex, Blue-Pirate, and Trace-viewer to capture and label in-vehicle data for validation of ADAS, infotainment, and connectivity systems. This work required a high level of attention to detail, accuracy in documentation, and the ability to interpret and classify data outputs across multiple hardware and software environments. My background also includes strong proficiency in Python, Bash, Linux command line, CAN/Ethernet communication protocols, and Jira/Confluence for issue tracking, which supports effective contribution to AI data workflows. I have collaborated cross-functionally with engineering, QA, and operations teams to ensure data integrity, reproducibility, and compliance with project standards. Combined with my academic training in Advanced Vehicle Systems, these experiences equip me with the technical and analytical foundation to support the creation, labeling, and validation of high-quality datasets for AI and machine learning applications.

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