Engineer Lead, Generative AI at Rappi

JANUARY 2024 - Present

• Leading a dedicated team of four, including Data Scientists and MLEs, to set project backlogs and provide technical guidance.
• Applied advanced AI-driven automation strategies, leading to substantial cost savings and financial consolidation at Rappi.
• Managed relationships with top-tier GenAI providers, ensuring integration and alignment with Rappi’s strategic goals.
• Developed and deployed advanced Retriever-Augmented Generation (RAG) systems.
• Simplified generative workload deployment by automating infrastructure setup, cutting time-to-production for language chains.
• Designed and developed LLM Agents using a graph-like architecture, employing advanced tooling to trigger various actions dynamically.

Key achievements:

• Led transformative generative AI projects, boosting efficiency and innovation across departments.
• Enabled access to advanced AI tools, impacting Rappi’s financial strength, with over 10 projects utilizing our services.

Teacher at CIBERTEC

DECEMBER 2023 - Present

• Instructed a bootcamp on Generative AI and Prompt Engineering, focusing on practical applications of Large Language Models (LLMs) in real-world scenarios.
• Co-created and taught a new course that incrementally guides students from foundational concepts to building a full MVP, incorporating LLMs, vector databases, and MLOps with hands-on projects.
• Developed and continuously updated engaging content that blends theory with practice, ensuring learners gain practical skills while staying current with the latest AI and tech advancements.

Machine Learning Engineer at Rappi

JANUARY 2022 - DECEMBER 2023

• Led an initiative focused on supporting LLM-based projects while also crafting an infrastructure platform to enable cutting-edge design patterns and solutions within the LLM field.
• Developed solutions that personalize product assortments to enhance engagement and satisfaction. Leveraged Airflow and Kubernetes to author automations that train machine learning models.
• Designed and implemented high-traffic APIs (Go) to deliver on-line recommendations. Conducted A/B experiments and data analysis on user groups to support evidence-based decision making.

Key achievements: Boosted CTR over 30% using recommendation systems. Constructed real-time engine for multi-model personalization support across teams that was featured in an AWS Case Study.

• Case study article on AWS
• Case study podcast on Spotify

Data Scientist at Belcorp

FEBRUARY 2021 - JANUARY 2022

• Built a predictive model based on time-series analysis to forecast cosmetic product tone/color preferences.
• Enhanced functionality and improved the performance of recommendation systems using PySpark.
• Tailored a collaborative filtering algorithm to meet diverse business requirements.
• Contributed to custom data science framework design and development, ensuring operational efficiency, support, and issue resolution within the personalization ecosystem.

Key achievement: Enhanced forecasting accuracy.

Data Engineering at Inetum, for Belcorp

JULY 2020 - FEBRUARY 2021

• Automated big data pipelines created in Apache Spark to compute and deliver offline metrics for model evaluation.
• Developed ETL processes to feed data visualization dashboards.
• Designed an improved workflow to operate an in-house developed recommendation model.

Key achievement: Improved efficiency by automating and optimizing manual processes.

Data Science Intern at Belcorp

OCTOBER 2019 - JUNE 2020

• Supported the development of a customer segmentation model.
• Performed EDA and feature engineering.
• Created query based reports to show business insights.
• Performed troubleshooting of a regression model in production.