Alfredo Estevez

Data Scientist, ML and AI Engineer

Hi, I'm Alfredo Estevez

I build AI that works on real business data. From classic machine learning to RAG agents, fine-tuned models, and MCP servers, built to last in production.

Mexico

About

Alfredo Estevez sitting on a ledge overlooking the Roman Forum

Hey 👋🏼 I'm Alfredo, an AI Engineer based in Mexico 🇲🇽. I began with robots and circuits as a Mechatronics Engineer, then fell for machine learning during my Master's and never looked back. Today I spend my days building with foundation models and cloud tools. When I'm not coding, you'll probably find me exploring new places or trying the newest coffee shop ☕

Recent Projects

Global Content Translator

Enroute · Client: Integral Ad Science · 2026

Localizes IAS’s customer-facing Help Center from English into 12 languages and keeps every translation in sync whenever the English article changes.

  • Translation time cut from ~2 hours (human-involved) to ~8 minutes (p50) per article.
  • Glossary-constrained Gemini enforces ad-tech terminology and preserves rich-text structure (links, headings, tables). A bulk backfill was followed by a Cloud Run webhook that republishes all locales on every English edit.
  • Vertex AI
  • Gemini
  • Cloud Run
  • Firestore
  • Contentful
  • Python

Contentful in Gemini Enterprise

Enroute · Client: Integral Ad Science · 2025–2026

Lets employees ask Gemini Enterprise plain-language questions about Contentful content and get sourced, linked answers, without learning the Contentful API.

  • An MCP server on Cloud Run exposes CMS data as structured tools, and a Python adapter turns them into Google ADK functions for Vertex AI Agent Engine.
  • Implemented a read-only guardrail that prevents the agent from writing to Contentful, and every answer returns source URLs.
  • MCP
  • Google ADK
  • Vertex AI Agent Engine
  • Cloud Run
  • TypeScript
  • Python

Scientific Literature Assistant

Datyra · Client: El Corporatus · 2024

A scalable RAG agent that answers questions over scientific literature, combining document search with structured SQL data.

  • PDFs in AWS S3 are loaded, cleaned, chunked, enriched with metadata and embedded into Chroma for semantic search.
  • Agent orchestrated with LangGraph, including safety and fallback nodes.
  • Served through asynchronous FastAPI microservices in Docker on AWS Fargate.
  • RAG
  • LangGraph
  • LangChain
  • ChromaDB
  • FastAPI
  • AWS Fargate
  • Docker

Multi-Label Harmfulness Classifier

Datyra · Client: Fooji · 2023

A fine-tuned LLM that scores user-generated text across nine dimensions of online toxicity, so brand community managers can enforce brand safety.

  • 94% F1 across all nine dimensions, with Llama-2 13B fine-tuned using QLoRA.
  • Trained on 500K texts from public datasets, APIs and custom scrapers, part of an 800K+ dataset spanning text, images and video.
  • Deployed on an Amazon SageMaker endpoint that Safesail calls for real-time toxicity scoring.
  • Llama-2 13B
  • QLoRA
  • HuggingFace
  • PyTorch
  • Amazon SageMaker

Experience

  1. AI Engineer

    Enroute

    Client: Integral Ad Science · Monterrey, Mexico

    Oct 2025 – Present

    • Built an AI-assisted translation pipeline for a Contentful-backed product: a webhook-triggered service translates changed fields across 12 languages with Vertex AI (Gemini) and writes back via the Contentful Management API, cutting translation time from ~2 hours (human-involved) to ~8 minutes (p50) per article.
    • Designed and shipped a multi-tenant AI assistant that answers natural-language questions about Contentful content, pairing an MCP HTTP server on Cloud Run with a Python agent on Vertex AI Agent Engine that routes per-user credentials through read-only operations.
    • Python
    • Vertex AI
    • Gemini
    • MCP
    • Cloud Run
    • Firestore
    • Contentful
  2. Data Scientist and AI Engineer

    Datyra Inc.

    San Diego, CA

    Apr 2021 – Aug 2025

    • Developed and managed a scalable RAG agent for scientific literature, combining structured SQL data, AWS S3 storage, asynchronous FastAPI services and Dockerized microservices on AWS, fed by a pipeline that extracts, cleans and vectorizes papers.
    • Migrated relational data (PostgreSQL) to BigQuery and added materialized views, cutting query times by up to 80%, automating CSV report delivery and enabling internal reporting through Looker Explores.
    • Built a data enrichment system on Google Cloud Functions that processed hundreds of Facebook leads, helping the marketing team allocate resources better.
    • Led data collection and labeling strategy, building three databases totaling 800,000+ data points (500k texts, 200k images, 100k videos) to train a harm detection AI for Safesail.
    • Fine-tuned a Llama-based LLM for harm detection, reaching a 94% F1 score across nine dimensions of text analysis, used by Fooji in its Safesail platform.
    • Python
    • FastAPI
    • AWS
    • Docker
    • BigQuery
    • Looker
    • Llama
    • LLM fine-tuning
  3. Software Engineer

    Visteon

    Querétaro, Mexico

    Aug 2019 – Feb 2021

    • Developed semi-automated Python software to run functional and regression tests on Ford vehicle cluster software over CAN communication, reducing testing time by 60% and automating Excel test report generation.
    • Python
    • CAN
  4. Junior Engineer

    Technological University of Mixteca

    Oaxaca, Mexico

    Oct 2018 – May 2019

    • Designed and simulated a chocolate tempering prototype machine using SolidWorks and MATLAB Simulink.
    • Collected experimental data to build a regression model that accurately described the system dynamics.
    • SolidWorks
    • MATLAB
    • Simulink
  5. Junior Engineer

    KATA, Solar Energy & Domotics

    Mexico

    Jul 2017 – Sep 2017

    • Built a relational database of solar energy components to improve the accuracy and speed of budget generation.
    • Developed an intelligent architecture on an STM32F4 microcontroller for a home automation gas monitoring system, enabling real-time detection and automated response to gas leaks.
    • STM32F4
    • Relational databases

Tech Stack

Programming

  • Python
  • C++
  • Go

AI & ML

  • TensorFlow
  • PyTorch
  • NumPy
  • Pandas
  • scikit-learn
  • Keras
  • HuggingFace
  • LangChain
  • LangGraph
  • LLMs
  • Prompting
  • MCP
  • Google ADK
  • RAG
  • MLOps

Cloud Platforms

  • AWS Lambda
  • AWS Fargate
  • AWS ECS
  • AWS CloudWatch
  • AWS S3
  • AWS SageMaker
  • GCP Vertex AI
  • GCP Firestore
  • GCP Cloud Run
  • GCP Pub/Sub
  • Azure
  • Docker

Databases

  • PostgreSQL
  • OrientDB
  • BigQuery
  • PgVector
  • ChromaDB
  • ElasticSearch

Tools

  • Jupyter
  • Linux
  • Looker
  • Tableau
  • REST APIs
  • FastAPI
  • Flask
  • Gunicorn
  • Contentful
  • Agile

Education

Degrees

  • Master of Science, Electronics Engineering and Artificial Intelligence

    Technological University of Mixteca · 2019 – 2021

  • Bachelor’s in Mechatronics Engineering

    Technological University of Mixteca · 2014 – 2019

Honors

  • CENEVAL National Award

    National academic excellence recognition

Certifications

  • EF SET English Certificate

    71/100 (C2 Proficient)

  • AI-Augmented Engineer, Professional

  • OOP and Algorithms with Python

  • ECMAScript 6+

  • Scrum Professional Course

Languages

  • Spanish

    Native or bilingual

  • English

    Full professional (EF SET C2)

  • Italian

    Elementary

Master’s thesis

Development and implementation of a Mexican Sign Language sign identification system based on neural networks and the Jetson Nano embedded system

Universidad Tecnológica de la Mixteca, Huajuapan de León, Oaxaca · 2022

Open access at the UTM repository ↗

Publication

Implementation and comparison of the KNN and CNN methods for the recognition of static signs of the Mexican Sign Language

UNAM SOMI ICAT · Oct 15, 2021

Compares a classical method (K-Nearest Neighbors) with a deep learning method (Convolutional Neural Networks) for recognizing static signs of Mexican Sign Language.

View ISSN record ↗