Open to opportunities

Jose Jo

@josejo

Message

I am a Machine Learning Engineer specializing in production AI solutions.

Guatemala

Message

What I'm looking for

I seek senior roles building production-grade ML/AI platforms (CV, NLP, GenAI) on cloud-native, scalable MLOps infrastructures, in collaborative teams that prioritize measurable impact and secure, compliant deployments.

I am a Machine Learning Engineer with 5+ years building Computer Vision, NLP, and GenAI solutions across healthcare, cybersecurity, retail, oil & gas, and biotechnology. I focus on architecting production-grade systems that bridge research and operational deployment.

I have led projects that delivered measurable impact: architected a dental CBCT imaging platform that reduced scan comparison time from 3–4 minutes to under 5 seconds and cut measurement errors by 28–30%, implemented retail object detection systems that improved accuracy by 30%, and developed a full‑stack RAG document intelligence platform that improved document processing efficiency by 45%.

My technical toolkit includes PyTorch, Python, TypeScript, React, VTK.js, Ray, Docker, MLflow, LoRA, YOLOv8, and cloud platforms (AWS, Azure, GCP). I build scalable data pipelines, distributed processing infrastructures, and secure, compliant solutions for sensitive domains.

I deliver end-to-end systems with an emphasis on performance, reproducibility, and security, and I thrive collaborating with cross-functional teams to move AI projects from prototype to production while ensuring regulatory and operational standards are met.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

Factored

Jun 2025 - Present (2 months)

Currently working as a Machine Learning Engineer. Responsible for building, architecting, and developing Computer Vision, NLP, and GenAI solutions for various industries.

PyTorch Python TypeScript React AWS Azure GCP Computer Vision NLP

Current

Machine Learning Engineer Consultant

Current

Grupo Lazquet

Feb 2022 - Present (3 years 6 months)

Developed a real-time object detection system for the retail industry using YOLOv8, PyTorch, and OpenCV, improving accuracy by 30%. Led an advanced computer vision project for the agroindustrial sector, implementing multimodal approaches with Google Vertex AI and Vision APIs.

YOLOv8 PyTorch OpenCV Vertex AI Ray AWS Lambda Docker Kubernetes fastAPI Python Tf.Data MLFlow Git

Senior Computer Vision/AI Platform Engineer

PearlAI

Nov 2024 - Present (9 months)

Architected an FDA-oriented dental CBCT imaging platform, reducing scan comparison time and measurement errors using BTKJS and React/TypeScript for real-time 3D visualization. Developed an interactive 3D/2D visualization system with VTK.js and OpenCV, optimizing performance for large dental datasets.

BTKJS React TypeScript VTK.Js OpenCV Docker Ray PostgreSQL Auth0 NiBabel PyTorch MLFlow AWS S3 Nibabel

Senior Data Scientist

Ernst & Young US

Sep 2023 - Present (1 year 11 months)

Built a predictive drilling and natural language query system for an oil and gas company using Azure OpenAI and Snowflake, reducing analysis time and improving model accuracy. Led three enterprise AI projects, acting as an Azure consultant and leveraging Azure OpenAI services.

Snowflake Python SQL Spark Docker Bicep MLFlow Azure Services Azure AI Document Intelligence Azure Blob Storage azure monitor GIS Tf.Data

Threat Intelligence Engineer

Sistemas Aplicativos

Aug 2021 - Present (4 years)

Conducted extensive research on machine learning models in cybersecurity using Python and NLP, developing threat detection services that enhanced offerings by 25%. Developed a brand protection service utilizing NLP to monitor the Dark Web, identifying and mitigating 40+ potential brand infringement cases.

Python NLP Cybersecurity Threat Detection Brand Protection Penetration Testing Data Analysis Incident Response

Data Science Consultant

Corporacion Lancasco

Jan 2020 - Present (5 years 7 months)

Conducted in-depth exploratory data analysis using Python and SQL for a pharmaceutical company, identifying top-selling sectors and products across 4 countries. Utilized advanced machine learning algorithms including XGBoost and Random Forest in Python to develop predictive models for product sales.

Python SQL Time Series Analysis XGBoost Random Forest Machine Learning

Education

Degrees, certifications, and relevant coursework

University Of The Valley

BSc, Computer Science And IT Engineering

Designed and implemented a fraud detection system for an insurance company using ML algorithms to automatically identify suspicious claims. Developed multiple classification models using Python, scikit-learn, and XGBoost achieving 90% accuracy, 0.80 AUROC, and 0.59 F1 Score in detecting fraudulent claims. Created a data preprocessing pipeline that handled imbalanced datasets and integrated with th