Ronald Pereira

- Led cross-functional AI initiatives and collaborated with key enterprise partners to co-develop innovative, high-impact solutions. - Pioneered the research and application of bleeding-edge AI, with a core focus on designing and implementing advanced LLM Agent workflows to solve complex challenges. - Established robust Data and ML Observability frameworks, utilizing advanced monitoring and metrics to ensure the reliability and peak performance of AI systems in production.

- Led technically a high-performing team in designing advanced machine learning systems to proactively prevent fraud, safeguarding iFood’s ecosystem while balancing risk mitigation with user experience. - Led and participated directly in several enterprise-wide Generative AI initiatives as the cross-functional GenAI lead, architecting solutions that redefined operational efficiency and customer engagement across the platform. - Pioneered the development of bleeding-edge multi-agent frameworks to solve complex business challenges, driving research from concept to scalable implementation. - Aligned fraud prevention and GenAI roadmaps with executive priorities, ensuring technical execution supported iFood’s long-term growth and market leadership. - Cultivated talent within the Data Science team through hands-on mentoring, helping them develop a more robust technical career path.

- Drove cutting-edge projects on iFood’s Disrupt team, conceptualizing and executing AI initiatives that redefined the platform’s capabilities and market positioning. - Architected an AI-powered dish recommendation engine in collaboration with Prosus, integrating user behavior analysis and business logic to personalize dining experiences at scale. - Pioneered an RL framework to automate A/B testing processes, streamlining experimentation workflows and enhancing data-driven decision-making for key business KPIs. - Partipated in projects from exploratory research to production deployment, including model design, validation, and integration with cloud-based infrastructure. - Partnered with product managers, engineers, and external stakeholders to align technical solutions with strategic business objectives, ensuring scalable and maintainable implementations.

- Participated directly in several fraud prevention initiatives by designing and deploying machine learning models to identify and mitigate fraudulent transactions, protecting company revenue and enhancing user security. - Owned the end-to-end development lifecycle of fraud detection systems, leveraging Python, PySpark (for big data analysis and feature extraction), and AWS SageMaker for seamless model deployment and monitoring. - Collaborated cross-functionally with engineering and product teams to integrate models into production systems, ensuring scalability and real-time performance in high-traffic environments. - Conducted rigorous analysis of model performance metrics to iteratively refine detection algorithms, improving precision while minimizing false positives. - Recognized for delivering a mission-critical fraud detection model that remains integral to iFood’s security infrastructure, praised for its sustained impact and reliability worldwide by Prosus.

On the acquisition by iFood.

- Engineered scalable back-end solutions using Go, Python, PHP, and C++, optimizing system performance and reliability for high-traffic applications. - Developed dynamic front-end interfaces with JavaScript, React.js, AngularJS, and Vue.js, alongside HTML5 and CSS3, enhancing user experience across multiple platforms. - Collaborated with cross-functional teams to deliver end-to-end features, ensuring seamless integration of front-end and back-end components. - Contributed to the maintenance and innovation of core products, streamlining workflows and reducing technical debt through codebase optimizations. - Gained hands-on experience in full-stack development within an Agile environment, balancing rapid iteration with long-term technical quality.

- Directed core administrative and financial operations, leveraging and further developing key skills in leadership, strategic communication, negotiation, and analytical decision-making. - Managed the organization's budget and financial planning and internal processes and resources allocation to ensure operational efficiency. - Actively contributed to several internal IT projects, showcasing versatility and a commitment to the company's core technological initiatives alongside directorial responsibilities.

- In my inaugural year, directly supported the Presidency Board, contributing to key organizational initiatives and external communications. - Actively engaged with several clients and partners, fostering relationships and representing the organization within a dynamic business environment. - Significantly developed persuasive communication and interpersonal skills through direct interaction with diverse stakeholders, enhancing client and partner engagement. - Played a key role in bridging communication between the organization and its external network, ensuring clear and effective information flow.

- Completed a Master of Science Degree in Computer Science at Federal University of Minas Gerais (UFMG) with Dr. Fabrício Murai as my advisor. - Focused my research on Fraud Prevention, specializing in Graph Neural Networks. My thesis was titled "Automatic Detection of Fraudulent Behavior in Networks using Graph Learning."

During my undergraduate years at the Universidade Federal de Minas Gerais (UFMG), I had the opportunity to engage in a diverse range of experiences: - I conducted biotechnology research under the mentorship of PhD Raquel Minardi at UFMG. - I utilized programming languages such as Python, Javascript, and Shell scripts to develop a project focused on classifying covalent interactions between hetero-atoms and protein atoms (2015/08 - 2016/08). - I authored two undergraduate theses, both centered on Machine Learning, with a strong emphasis on semi-supervised models. - I successfully executed numerous projects in the field, applying various concepts including Natural Language Processing, Computer Vision, Deep Learning, Recurrent Neural Networks, clustering, classification, causality, and interpretable models. These experiences played a pivotal role in shaping my understanding and expertise in Computer Science during my undergraduate journey.

Won several Best Student awards.