Machine Learning Engineer
Building applied ML systems that move from research to production.
I work across forecasting, NLP, agentic workflows, and production ML infrastructure.
Experience
Applied ML, product engineering, and research.
Production forecasting, research-grade neural networks, and NLP systems built for real workflows.
Machine Learning Engineer
Current role
April 2023 - Present
Colombia
- Working with agentic AI and LLM pipelines for internal workflows.
- Contributed to forecasting-oriented work, including event prediction and deployment.
- Built and deployed ML services with FastAPI on AWS using Docker and SQL-backed workflows.
Machine Learning Researcher
University of Toronto
May 2022 - August 2022
Toronto, ON
- Simulated crystal structures in PyTorch with Crystal Graph Convolutional Neural Networks to support new materials discovery.
- Ran neural network pipelines on cloud clusters with large crystallography datasets and contributed to a research paper.
- Investigated datasets such as Materials Project to understand structure-property relationships in materials science.
Software Engineer
Guane Enterprises
May 2020 - April 2023
Colombia
- Built an AI workflow to extract pricing data from documents with Python, Pandas, and ML tooling, reducing manual effort for a large logistics company.
- Implemented NLP extraction pipelines, including named entity recognition, and exposed them as FastAPI services.
- Deployed APIs with Docker and Kubernetes and collaborated with clients in the United States.
Engineering Intern
Guane Enterprises
February 2020 - May 2020
- Deployed microservices to Google Cloud Platform and improved Python services with FastAPI.
- Used Docker to create and package containerized applications.
Portfolio
Selected builds across RAG, simulation, generative systems, and game AI.
ML prototypes, technical builds, and experiments that show how I think end to end.
Game Intelligence
Smart Tetris
Game AI project exploring automated decision-making inside a classic Tetris environment.
Retrieval + LLMs
RAG Transito
Retrieval-augmented assistant work focused on LLM orchestration for answering questions about traffic laws.
Publication
Navigating Materials Space with ML-Generated Electronic Fingerprints
Materials ML research produced during work at the University of Toronto and published on ChemRxiv.
Channel
YouTube
Videos on machine learning, software builds, and technical experiments.
Interactive Simulation
Physics Lab
Interactive web project for physics exploration and visual, hands-on experimentation.
Neuroevolution
Deep Genetic Snake
Experimental game-agent work around evolving behavior in a snake environment.
Generative Pipeline
NFTs Images Generator
Full-stack experiment that periodically generates new visuals and publishes them through a frontend and backend workflow.
Education
Formal training in physics, software, and applied AI.
The academic base is physics, but the practical emphasis has been machine learning, software engineering, experimentation, and technical communication.
Degree
BSc in Physics
Universidad de Antioquia
Thesis: Applying Transformers to Naval Route Prediction.
Awarded Academic Honors three times for the highest semester GPA in my cohort.
Relevant Coursework
Additional Learning
- Deep Learning Specialization, Coursera (January 2020)
- Building Generative AI Applications with Amazon Bedrock
- Amazon DynamoDB for Serverless Architectures
Recognition
- 2016 Iberoamerican Physics Olympiad Bronze Medal
- International Physicists' Tournament (IPT) 2019, College Round Winner