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Bruno Barbosa Cerqueira

@brunobcerqueira

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Data scientist specialized in deep learning, computer vision, and MLOps.

Brazil

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What I'm looking for

I seek roles building and deploying interpretable, scalable AI systems—especially in computer vision and MLOps—with collaborative teams that value research-driven, production-ready solutions and opportunities for technical leadership.

I am a data scientist with a strong foundation in deep learning, computer vision, and MLOps, built on academic training in astrophysics and engineering. I design and deploy scalable AI solutions, training CNNs and Vision Transformers for scientific and applied tasks.

My master's research produced automated multiband datasets, multi-target regression models (global MAE = 0.032), and classification models achieving an F1-score of 75.5% (internal) and 86.4% accuracy on independent tests. I apply interpretability methods such as SmoothGrad and perturbation analysis to make models more transparent.

I deliver end-to-end pipelines and production-ready deployments using MLflow, Docker, FastAPI and orchestration tools, and I have built AI agents integrated with APIs and n8n for workflow automation and reporting.

Experience

Work history, roles, and key accomplishments

Current

MLOps / Applied AI Engineer

Current

Independent Projects

Built end-to-end ML pipelines and deployments including a customer churn prediction system (RF accuracy 95.5%) and intelligent agents using GPT API and n8n for workflow automation with PostgreSQL and Docker-based deployments.

MLFlow Docker fastAPI Random Forest PostgreSQL N8n API Integration CI CD Python

Researcher – Master's Thesis

Institute of Astrophysics and Space Sciences

Jun 2023 - Jun 2025 (2 years)

Led development of CNN and Vision Transformer models to identify Lyman-α emitting galaxies, achieving F1-score 75.5% on internal validation and 86.4% accuracy on independent testing; implemented multi-target regression with global MAE 0.032 and applied interpretability techniques to analyze activations.

Python TensorFlow Keras CNN Vision Transformer Explainable AI Pandas NumPy

Researcher – Research Fellowship

Institute of Astrophysics and Space Sciences

Sep 2022 - Jun 2023 (9 months)

Developed deep learning models (CNNs, Visual Transformers) for classification and regression in the Finding Lyman-Alpha Emitters project and co-authored a related peer-reviewed article.

Python PyTorch TensorFlow CNN Vision Transformer Experiment Design Git

Education

Degrees, certifications, and relevant coursework

University of Porto

Master of Science, Astronomy and Astrophysics

2023 - 2025

Activities and societies: Elective courses in Introduction to Data Science and Machine Learning; master's thesis research at the Institute of Astrophysics and Space Sciences.

Master’s in Astronomy and Astrophysics with a thesis applying neural networks to study Lyman-alpha photon escape conditions.