• With over 15+ years of experience as an AI Generative Architect, I bring a strong foundation in mathematics, MLOps, and advanced cryptography and blockchain technologies.
• Holding a Ph.D. in Philosophy of Science, which enriches my approach to complex problem-solving in tech innovation.
• Proven track record in transitioning Proof of Concepts into scalable, cloud-based production solutions.

Languages: Mathematics, Python, C#, Solidity
AI/ML: MLflow, Amazon Bedrock, PySpark, PyTorch, Tensorflow, Scikit-learn, Hugging Face, LangChain,
Blockchain: Ethereum, Truffle, Hardhat, Cryptography
IoT: Arduino, Raspberry Pi
Database: MySQL, MongoDB, Pinecone
Creative Tools: Unity3D, Unreal Engine
Version Control: Git

Deep Learning Architect, Generative AI Innovation Center

Amazon Web Services (AWS) - Consultant
Timeline: Jan 2024 – Present

Responsibilities: As a Deep Learning Architect at AWS, I work on the forefront of AI, specializing in developing and implementing Generative AI solutions. My key responsibilities include:

• Collaborating with clients to identify their business challenges and crafting tailored AI solutions that deliver measurable value.
• Leading research and experimentation on new algorithms, optimizing systems to enhance risk management, profitability, and customer experience.
• Ensuring the scalability and efficiency of systems to manage large datasets and meet high-demand requirements.
• Advising on best practices for the responsible and cost-efficient application of Generative AI across various industries.

SNI Researcher – Professor

El Colegio de México
Timeline: Aug 2017 – Jan 2024

Descriptions: In my role as a SNI Researcher and Professor at El Colegio de México, I focus on advancing social research through the integration of AI and Big Data. My current research employs PyTorch, Computer Vision, and Big Data tools (like PySpark), alongside qualitative methodologies, to examine social mobility related to skin tone in Mexico. This innovative approach has attracted international media attention and resulted in five published papers that have significantly influenced discussions and policies regarding social equality and mobility within the country.

AI Generative Engineer (Sr.)

Amber Studio
Timeline: Feb 2023 – Dec 2023

Descriptions: In my role as an AI Generative Engineer at Amber Studio, I focused on revolutionizing 3D content generation through advanced AI techniques. I led the design and development of an AI pipeline for automated 3D content generation, utilizing cutting-edge models such as Stable Diffusion, LLM, NeRF, and Gaussian Splatting within an MLOps framework.

Key Projects:

• Text-To-3D Tool Development (Unreal Engine): I spearheaded the creation of a Text-To-3D tool integrated with Generative AI models for Unreal Engine, significantly improving the 3D asset creation process for the Unreal for Fortnite (UEFN) platform. This innovation reduced costs from $43.00 to $1.94 per item, streamlining production and enhancing efficiency.

AI/ML Pre-Sales Engineer

bSide Solutions (Microsoft Gold Partner)
Timeline: Nov 2019 – Jun 2022

Descriptions: In my role as an AI/ML Pre-Sales Engineer at bSide Solutions, I collaborated closely with the sales team to develop AI and ML-based Proofs of Concept (PoCs) and Minimum Viable Products (MVPs), showcasing Microsoft’s technology capabilities through AzureML.

Key Achievement:

• Face Identification System for Raspberry Pi Check-Ins: I designed and implemented a high-efficiency face identification solution using Azure’s Face API, which was fine-tuned with TensorFlow for Raspberry Pi. This innovative system significantly enhanced security measures and streamlined process efficiency for check-in procedures.

Artificial Intelligence Engineer Sr

Trackstreet
Timeline: Oct 2018 – Oct 2019

Descriptions: In my role as an Artificial Intelligence Engineer at Trackstreet, I harnessed AI to create smarter business solutions. I utilized Natural Language Processing (NLP) tools such as spaCy and NLTK to extract valuable insights about users, which informed future marketing campaigns. Additionally, I developed recommendation systems using PyTorch and VectorDB to minimize brand and pricing policy violations. My position also involved collaborating remotely with an international team of five data scientists, employing MLOps practices to enhance our data science workflows and improve project efficiency.

Data Science Lead

Klustera
Timeline: Jan 2017 – Oct 2018

Descriptions: As Data Science Lead at Klustera, I spearheaded a project for OCESA, a major Latin American festival promoter, focusing on tracking attendee movements at concerts. This project utilized Kafka for streaming data management, combined with CNN-based computer vision and WiFi sensor data. We implemented autoencoders for filtering sensor data and used PyTorch for AI-driven movement prediction. My role was crucial in deriving analytics that improved event management and enhanced the attendee experience.

Creative Technologist Lead

Random Interactive
Timeline: Jan 2011 – Jan 2017

Descriptions: In my role as Creative Technologist Lead at Random Interactive, I directed the selection and implementation of development strategies and technologies for major projects. A notable project included the creation of an interactive art installation utilizing motion detection technology to display 3D avatars of military ranks and uniforms. This project responded to visitors' movements through the integration of Kinect sensors with Python and Unity3D. Additionally, I played a pivotal role in client communications, effectively conveying complex technical and creative concepts, which facilitated a clear understanding of project objectives, garnered positive client feedback, and ensured successful project delivery.

iOS Developer

Ironbit
Timeline: Jul 2009 – Dec 2010

Descriptions: As an iOS Developer at Ironbit, I contributed to the development of the ‘Televisa Deportes’ app, which became the most downloaded app in the Mexican App Store in 2010. My primary responsibility involved engineering the streaming video component of the app, employing Core Media and Multithreading with Grand Central Dispatch to optimize performance. This effort resulted in a significant 38% improvement in streaming efficiency, enhancing both user experience and overall app performance.