As a strategic leader in AI operations, I spearheaded foundational annotation projects that were instrumental in the development of MetaAI’s multimedia capabilities and the successful launch of the Llama 4 Reasoning Model. Managing a combined portfolio of $65M ($45M STEM/non-STEM and $20M multilingual), I directed the end-to-end delivery of high-volume datasets while maintaining rigorous quality standards.

I specialized in scaling technical operations, most notably driving an accuracy increase from 60% to 90% across 1.7M annotations through re-engineered QA protocols, automation, and targeted data analysis. By directing image and video annotation initiatives, I enabled robust content understanding and advanced Omni-model capabilities. My work went beyond data delivery; I acted as a product architect, optimizing custom tooling UI layouts and refining operational guidelines from initial concept to scalable workflow designs.

A key pillar of my leadership was driving strategic alignment. I unified visual text and LLM tone initiatives under a single media framework, which eliminated silos, fostered cross-functional synergy, and provided leadership with a clear, consolidated view of AI advancements. To support these initiatives, I managed complex vendor relationships and collaborated with subject matter experts to resolve blockers and source critical datasets, including essential data for five at-risk languages to support global preservation.

Whether coordinating with GenAI teams on guideline updates or managing performance metrics for large-scale labeling teams, my focus remained on bridging the gap between ambitious research goals and high-velocity execution. By aligning processes with evolving model requirements, I ensured that Meta’s AI initiatives were fueled by the high-fidelity data necessary for industry-leading performance.

I specialized in leading end-to-end data integration and feature implementation projects for enterprise-level clients, with a primary focus on maintaining high standards for on-time delivery and strict SLA compliance. My role served as a technical bridge between client ecosystems and core platforms, where I managed complex vendor workflows to facilitate seamless API integrations between various CRM systems and Data Management Platforms (DMP).

As a technical consultant, I guided strategic clients through the complexities of platform onboarding, CRM connectivity, and rigorous data security assessments. Beyond implementation, I acted as a key advisor to product teams, translating client feedback into actionable feature enhancements for both Demand Side Platforms (DSP) and DMPs to drive operational efficiency and long-term retention. To ensure scalable success, I also established and maintained a centralized repository of technical documentation and bespoke integration solutions tailored for high-value strategic partners.

I specialized in scaling high-quality data collection and labeling operations to support foundational Computer Vision goals. My role focused on the intersection of vendor management and technical execution, where I oversaw daily operations, established performance metrics, and led the development of comprehensive training guidelines for global labeling teams. By acting as a central coordinator, I ensured that data efforts remained strictly aligned with AI product requirements and broader organizational strategies.

Through rigorous data analysis, I identified critical bottlenecks in underperforming projects, implementing targeted solutions that optimized throughput without compromising accuracy. I worked closely with cross-functional stakeholders to define team objectives, execute operational strategies, and provide transparent reporting on project progress. My contributions were essential in building the scalable, high-fidelity data pipelines necessary to train and refine sophisticated Computer Vision models.