Rodrigo A.

Data Engineer

AI Engineer
1/1/2024 - Present

Developed advanced expertise in creating machine learning and deep learning algorithms. Leveraged generative AIs for various applications, enhancing predictive analytics and automation processes. Demonstrated proficiency in utilizing frameworks such as TensorFlow, PyTorch, and Keras to design and optimize complex neural networks. Executed model training, validation, and deployment using extensive datasets. Applied techniques like supervised learning, unsupervised learning, and reinforcement learning to solve diverse problems. Incorporated cutting-edge methodologies like GANs (Generative Adversarial Networks) to improve model performance. Employed tools such as Jupyter Notebook, Python, and R for data analysis and model development. Ensured continuous model monitoring and iterative improvement through feedback loops and performance metrics. Collaborated with cross-functional teams to integrate AI solutions into existing systems, significantly enhancing operational efficiencies and decision-making processes.

professor
12/1/2023 - Present

Led the graduate program in machine learning engineering, developing and delivering advanced course material that covered a range of machine learning algorithms, data processing techniques, and statistical analysis methods. Demonstrated proficiency in Python, R, and MATLAB for statistical computing and machine learning model development. Utilized frameworks and libraries such as TensorFlow, Keras, PyTorch, and scikit-learn to instruct on the design, implementation, and optimization of machine learning models. Emphasized the importance of data preprocessing and feature engineering, employing tools such as Pandas and NumPy for efficient data manipulation. Instructed students on the application of SQL and NoSQL databases, including PostgreSQL and MongoDB, to manage large datasets. Fostered collaborative and reproducible research practices using version control systems like Git and project management platforms such as Jupyter Notebooks. Guided students through real-world projects, reinforcing principles of supervised and unsupervised learning, model evaluation metrics, and deployment strategies. Additionally, integrated cloud computing resources and services, including AWS and Google Cloud, to teach scalable machine learning model deployment and maintenance.

Data Scientist
2/1/2022 - 1/1/2024

Developed proficiency in conducting exploratory analyses, statistics, and Optical Character Recognition (OCR) using Microsoft Azure. Demonstrated expertise in extracting text from images, data augmentation, and training machine learning, deep learning, and Natural Language Processing (NLP) models. Utilized object-oriented programming in Python to develop and enhance algorithms. Focused on increasing efficiency and profitability by creating tools grounded in agile methodologies. Achieved continuous improvement of predictive algorithms through extensive testing of various machine learning models. Implemented optimal models tailored to specific projects by leveraging automation with Lazy Predict and versioning with ML Flow.

Production Engineering at UNILASALLE
2016 - 2021

Artificial Intelligence at Federal University of Rio de Janeiro
2022 - 2024

Data Science at Lets Code Academy
2021 - 2022

ANCORD at FGV
6/1/2021