Lead end-to-end global data collection initiatives that power AI and ML models for Meta’s Product Data Operations (Wearables), including Ray-Ban Meta smart glasses. Drive internationalization (i18n) strategy by scaling language support across dozens of markets, enabling product expansion and new market entry.

Manage large-scale, multi-country programs, coordinating on-device and crowdsourced efforts across vendors and facilities worldwide. Oversee budgets, optimize resource allocation across regions, and ensure compliance with international legal and privacy requirements.

Partner cross-functionally with product, legal, privacy, security, and vendor operations teams to deliver millions of high-quality datasets used to train and evaluate AI models.

(@ Magnit on assignment at Meta.)

• Project Management: Track and monitor project progress to ensure deadlines are met and promptly address any project needs within the GenAI for Reality Labs, AI/ML Wearables, and Smart Glasses domains.

• Scheduling & Logistics: Assist in scheduling and logistical coordination for projects, ensuring seamless execution.

• Rapid Response Coordination: Serve as the primary point of contact for the rapid response team, ensuring swift and efficient issue resolution.

• Training & Development: Develop and conduct comprehensive training sessions for team members and stakeholders, enhancing overall team capabilities.

• Audits & Quality Checks: Conduct audits and quality checks to ensure high standards and compliance with project requirements.

• Communication Facilitation: Foster effective communication between team members and management to ensure project alignment and success across GenAI for Reality Labs, AI/ML Wearables, and Smart Glasses projects.

Enhance tooling and test new features to improve GenAI data annotation workflows. Develop training content and host webinars for onboarding new contributors, playing a key role in identifying and resolving quality challenges within the GenAI data pipeline. Collaborate with stakeholders to ensure data integrity and utilize data visualization tools to drive high-quality project delivery and contributor performance.

Training artificial intelligence models for improved writing, creating challenging AI prompts, evaluating and ranking AI-generated responses, assessing safety and bias, ensuring factual accuracy, and contributing to the enhancement of internal software for data annotation workflows.

Translation, creation, enrichment, and validation of knowledge bases and taxonomies in Brazilian Portuguese (PT-BR). Identifying systematic relationships between concepts such as job titles, skills, certificates, etc. Researching, classifying, and annotating the phrases, terms, and data in messy, user-generated data. Research new entity categories and best practices for organizing them. Leverage external resources and standards to enrich and organize data.