Professional Overview
**Computer Systems Engineer** with a strong interest in Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision. Experienced in Python, PyTorch, TensorFlow, and FastAPI through academic and personal projects. Passionate about building AI-driven solutions, continuously learning new technologies, and contributing to real-world m
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Developed a facial emotion recognition model with EfficientNet-B2 and PyTorch.
- Built a Spanish emotion analysis module using the RoBERTuito model.
- Developed REST APIs with FastAPI for AI model inference.
- Integrated AI services with React and Spring Boot.
- Evaluated deep learning models using classification metrics.
Key Achievements / KPIs
- Built end-to-end AI modules for facial and text emotion analysis.
- Applied transfer learning with EfficientNet-B2 for image classification.
- Integrated AI models into a full-stack web application using FastAPI.
- Completed an AI-based academic project from model training to deployment.
Education
Field of Study: Computer Systems Engineering
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
