Control Systems · AI/ML · Aerospace

Guilherme
Paiva

guifnpaiva@hotmail.com
+55 (35) 99920-5864
linkedin.com/in/guifnpaiva
▸ São José dos Campos, Brazil
Professional Summary

About me

Control and systems engineer with 4+ years at Embraer in aerospace and defense product development — spanning control law design, model-based engineering, simulation, requirements analysis, system integration, and V&V. Currently pursuing an M.Sc. at ITA researching learning-based control and data-driven modeling of nonlinear dynamical systems.

Core Skills
Control & Systems
Control Engineering State-Space Methods Nonlinear Systems Model-Based Design MATLAB Simulink V&V Rational DOORS
Software & Embedded
Python C++ C Qt Linux Git / GitHub Flutter BLE
AI / ML & Data
TensorFlow TensorFlow Lite scikit-learn Neural Networks CNN Edge AI Computer Vision
Engineering Tools
JIRA Rational DOORS System Integration Technical Docs Requirements Analysis
Languages
Portuguese Native
English Full Professional
Work History

Experience

Product Development Engineer 2× Award Winner Apr 2023 — Present
Embraer — Aerospace & Defense · São José dos Campos
▶ Show details
  • Lead product development for complex aerospace and defense systems, coordinating system integration, V&V, engineering analysis, and multidisciplinary technical decisions.
  • Develop and evaluate MATLAB/Simulink simulation models for model-based design, system behavior analysis, design trade-offs, and technical reviews.
  • Translate operational needs into traceable system requirements and engineering solutions across systems, software, integration, and test teams.
  • Support requirements analysis, system-level reviews, verification evidence assessment, and technical documentation in Rational DOORS and JIRA.
  • Earned Embraer Engineering Awards in 2025 (Product Solutions) and 2024 (Lean and Agile Thinking).
Product Development Analyst Oct 2022 — Apr 2023
Embraer — Aerospace & Defense · São José dos Campos
▶ Show details
  • Contributed to system integration and verification activities for aerospace and defense programs, including engineering analysis, technical documentation, and system-level assessments.
  • Assisted in development and evaluation of MATLAB/Simulink simulation models to support product development workflows and system behavior analysis.
  • Reviewed requirements and test evidence in Rational DOORS, improving traceability between requirements, verification artifacts, and engineering decisions.
Engineering Intern Oct 2021 — Oct 2022
Embraer — Aerospace & Defense · São José dos Campos
▶ Show details
  • Supported control law development using MATLAB/Simulink, including modeling, simulation, and functional evaluation of control system components.
  • Assisted V&V tasks through test case execution, results analysis, and documentation of evidence for system-level assessments.
  • Worked with senior systems engineers on requirements analysis, traceability activities, and engineering documentation using DOORS.
Mobile Developer Intern Feb 2021 — Oct 2021
INNATIS France / Eurofeedback Brasil · Santa Rita do Sapucaí
▶ Show details
  • Developed a cross-platform iOS/Android app in Flutter connected to a bioimpedance measurement device via Bluetooth Low Energy (BLE).
  • Implemented BLE device discovery, connection handling, data exchange, backend API integration, and local data storage.
  • Collaborated in an international project environment involving mobile development, hardware-software integration, and user-facing measurement workflows.
Selected Work

Projects

M.Sc. Research · ITA · 2024–Present
AI-Assisted Control & Data-Driven Modeling for Nonlinear Dynamic Systems
Research on learning-based methods for modeling, simulation, and adaptation in complex dynamical systems, with focus on stability, robustness, and interpretability.
MATLABSimulinkPythonNonlinear ControlNeural Networks
Embraer · Nov 2024–Jun 2025
Radar Signal Processing & Matched Filter Simulation
Radar simulation workflow covering chirp waveform generation, RF channel modeling, downconversion, and matched filtering analysis.
MATLABSimulink
Inatel · Jan–Dec 2022
Coffee Leaf Disease Classification — Embedded CNN Mobile App
Trained and deployed MobileNetV2 CNN for coffee leaf disease classification, achieving 99.65% test accuracy. Converted to TensorFlow Lite for on-device inference in a Flutter app.
PythonTensorFlowTF LiteFlutterDart
Engineering Project · Jul 2022–Oct 2023
Embedded PDF Reader & Document Visualization Application
C++/Qt embedded application for PDF rendering and document visualization in a constrained engineering environment, optimized for Linux compatibility and performance.
C++QtLinux
Academic Background

Education

Certifications
Python Journey: Machine & Deep Learning FIAP SHIFT Apr 2026 · 101 hours · ID 128936173
Machine Learning Stanford University / Coursera Jun 2021 · Verify ↗
Recognition

Awards

🏆
Embraer Engineering Award — Product Solutions Category
Embraer · 2025
🏆
Embraer Engineering Award — Lean and Agile Thinking Category
Embraer · 2024