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Wanderson souza

PhD, AI DEVELOPER & MACHINE LEARNING ENGINEER
  • Curriculum Vitae
  • github
  • Gmail

Hi, I'm Wanderson

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I am a Senior Machine Learning Engineer and Data Scientist with a strong academic background (PhD in Mechanical Engineering and BSc/MSc in Computer Science) and over 8 years of experience developing AI solutions applied to real-world business problems.

Since 2017, I have worked on projects in Computer Vision, Natural Language Processing (NLP), and more recently LLMs and intelligent agent-based systems, with a strong focus on scalable, governable, and value-driven architectures.

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I am currently part of the Motiva team, where I work on cloud architecture design, the development of data- and AI-driven solutions, and the automation of processes through LLM-based agents. My work includes consolidating multiple initiatives into integrated ecosystems, standardizing CI/CD pipelines, enabling reusable components, and integrating services across Azure environments.

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I have hands-on experience building Agentic RAG pipelines, combining Python, n8n, and cloud services to deliver secure, traceable, and reliable document processing, including structured OCR, embedding generation, and the application of validation and security policies over LLMs.

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Beyond hands-on development, I provide technical leadership and strategic guidance, working closely with business stakeholders to translate requirements into viable architectures. I operate end-to-end, from architectural design to deployment, prioritizing scalability, traceability, and operational reliability.

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EXPERIENCE
EXPERIENCE

Latest experiences

2025 - Current

Tech Leader | AI Specialist

MOTIVA

I lead AI initiatives focused on cloud-native architectures, LLM-based agents, and intelligent automation, designing end-to-end solutions on Azure. My work includes building agentic RAG pipelines, standardizing CI/CD, and enabling scalable, cost-aware AI ecosystems integrated with business processes.

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2024

Machine Learning Engineer

VENTURUS

I developed infrared face recognition, led the Merge Model for multi-object detection, and currently lead the AI Security project focused on liveness detection and iBeta certification.

2023

Machine Learning Engineer

ITRIAD

I worked on head pose estimation and model compression for embedded systems, applying quantization and architecture simplification to deploy efficient models on low-resource devices.

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2022

Data Scientist

NEOPTO

I worked as a data scientist at the NeoPTO Intellectual Property. We are developing a system in the information retrieval area that assists in the semantic search process for patents based on the evolution of trends passed by the user.

2021

Data Scientist

LACINA

I worked as a data scientist at the Applied Intelligence and Computation Lab (LACINA). We have developed a multilabel supervised system for hierarchical patent classification with more than 270,000 classes.

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2020

Researcher and Machine Learning Engineer

GPICEEMA (INSTRUMENTATION AND CONTROL GROUP IN ENERGY AND ENVIRONMENT STUDY)

I worked as a machine learning engineer and researcher at the Solar Energy laboratory at the Center for Alternative and Renewable Energies at UFPB and I am part of the Instrumentation and Control Group in Energy and Environment Studies (GPICEEMA) developing solutions with computer vision.

2015-2019

Machine Learning Specialist

METROREC / CBTU-JP

I worked between 2015 and 2019 as a researcher and machine learning specialist in the partnership between UFPB and METROREC / CBTU-JP. Throughout this period, I developed the VisionBerry project, in which we developed a computer vision system to estimate the multidirectional flow of passengers in subway transportation using embedded devices.

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2017-2019

Research and Professor

IFPB (FEDERAL INSTITUTE OF PARAÍBA)

I was a professor of computer science and scientific methodology, teaching classes on programming basics, advanced Excel, and operating systems for technical education classes.

EDUCATION
EDUCATION
2015-2019

Doctor of Sciences

UFPB (FEDERAL UNIVERSITY OF PARAÍBA)

I am a D.Sc in Mechanical Engineering. Throughout this period I developed a passenger estimation system using deep neural networks. In October 2017, the results of the VisionBerry project earned me participation in the Empreenda Santander contest in the technological innovation category and I reached the semi-final.

2011-2013

Master of Science

2004-2009

Bachelor of Science

UEPB (STATE UNIVERSITY OF PARAÍBA)

B.S. in Computer Science at the State University of Paraíba

SKILLS
SKILLS
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Development

Extensive experience with Python, with a strong background in developing end-to-end machine learning solutions. I have worked with the full ML stack since 2017, including libraries such as NumPy, pandas, PySpark, matplotlib, scikit-image, SciPy, TensorFlow, Keras, and PyTorch.

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Leadership

I lead AI projects from planning to deployment, coordinating teams, managing backlogs, and aligning technical goals with business needs. I value clear communication, autonomy, and a results-driven mindset.

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Software engineering

I take use of design patterns, code review techniques, documentation, respecting the pep8 style guide and other important concepts to improve code readability and maintenance.

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Proactivity

I'm a proactive person, compromised and responsible with my work. Attributes that I believe that all developers must have in order to be a quality professional.

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Team work

I thrive in collaborative environments and have experience leading cross-functional teams in machine learning projects. I use GitHub and GitLab for version control, and I encourage the use of productivity tools to streamline workflows, improve communication, and ensure project alignment across the team.

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High academic background

I have a high qualification, papers published in the area and teaching experience.

SPECIFIC SKILLS

  • 🧠 Models & Architectures

    • YOLOv5

    • YOLOv7

    • ResNet

    • MobileNet

    • MobileFaceNet

    • ConvNeXt

    • Transformer

    • Vision Transformer

    • Llama

    • GPT-4

    • Deepseek

  • 🎯 Loss Functions

    • Binary Cross-Entropy (BCE)

    • Cross-Entropy

    • Focal Loss

    • Contrastive Loss
    • Triplet Loss
    • ArcFace, CosFace and Loss
    • MAE/MSE (For regressive tasks)

  • 📚 ML & Data Science Stack

    • OpenCV

    • matplotlib

    • scikit-image

    • scikit-learn

    • NLTK

    • SciPy

    • Numpy

    • Pandas

    • PySpark

    • PyTorch

    • Tensorflow

  • ⚙️ MLOps, Infra & Tools

    • Docker

    • Kubernets

    • minIO

    • AirFlow

    • MLFlow

    • Grafana

    • Github Actions

    • CI/CD

    • N8N

    • Azure

    • AWS

    • GCP

  • 📦 Model Optimization & Compression

    • TensorRT

    • SigmaStar Framework

    • Quantization

    • Pruning

    • Knowledge Distillation

  • 🧩 Core Skills

    • Strong background in mathematics and analytical reasoning

    • Effective teamwork and communication

    • Experience in project ownership, backlog planning, and interfacing with stakeholders

    • Ability to design creative solutions in non-standard scenarios

  • 📁 Projects

    • VisionBerry – Passenger flow estimation using computer vision

    • AI Patent – Patent classification using hierarchical NLP models

    • IP Search – Semantic information retrieval for patent databases

    • Head Pose Estimation – Predicting head position for embedded deployment

    • Pixsee Guard – Infrared face recognition for low-light conditions

    • Merge Model – Unified object detection model (body, face, pets, dolls) for edge devices

    • AI Security – Anti-spoofing system with RGB and IR liveness detection, targeting iBeta certification

    • Model Optimization – Quantization, pruning, and distillation for embedded AI

    • Nexus – Embedded LLM-based assistant for TV environments

    • CSC - Cloud-based AI system for operational monitoring and intelligent automation, using LLM-based agents to correlate events and generate actionable insights.

    • Root Cause - AI-driven root cause analysis platform, combining machine learning and agentic RAG to support legally oriented processes with traceability and evidence-based reasoning.

COURSES & CERTIFICATIONS
COURSES
Image by Kiyun Lee

  • Build Generative Adversarial Networks (GANs) by deeplearning.ai

  • Python for Data Science and AI by IBM

  • Machine Learning with Python by IBM

  • Introduction to Deep Learning & Neural Networks with Keras by IBM

  • Deep Neural Networks with PyTorch by IBM

  • Building Deep Learning Models with TensorFlow by IBM

  • AI Capstone Project with Deep Learning by IBM

  • Math for Machine Learning by AWS

  • Natural Language Processing by Kaggle

  • Natural Language Processing with Classification and Vector Spaces by deeplearning.ai

  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai

  • Structuring Machine Learning Projects by deeplearning.ai

  • Exploring and Preparing your Data with BigQuery by Google Cloud

  • Scrum Fundamentals Certified by SCRUMstudy

  • LLM Engineering: Master AI, Large Language Models & Agents by Udemy

  • Introduction to quantum computing by Tic em Trilhas (on going)

CONTACT

Wanderson Souza

MACHINE LEARNING ENGINEER

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Phone:

+55 (83) 98857-9083

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E-mail:

wandersonsouza.info@gmail.com

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  • github

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© 2026 por Wanderson Souza.

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