Machine Learning Frameworks

A highly skilled professional in Electronic Engineering with a strong focus on Computer Vision and Artificial Intelligence, possessing robust qualifications through a Bachelor's and ongoing Master's degree in Electrical Engineering. Demonstrated expertise in image processing, object detection, anomaly classification, and semantic segmentation utilizing advanced frameworks such as PyTorch, TensorFlow, and OpenCV. Current research as an AI & Computer Vision Researcher involves developing software to inspect visual defects in notebooks using sophisticated techniques aligned with Agile methodology. Proficient in handling various communication protocols and embedded systems, combined with practical experience in natural language processing and thermographic imaging solutions. A commitment to innovation is evidenced by participation in international educational programs and ongoing professional development in cutting-edge technologies.

With a background in Chemistry from UnB, and currently completing degrees in Big Data and an MBA in Data Science and Analytics, this professional has been actively engaged in artificial intelligence since 2022. Demonstrating expertise in computer vision, natural language processing, and recommendation systems, experience includes hands-on roles as an AI Developer at Apollo Solutions Dev and Cromai, focusing on developing applications with LLMs, ETL processes for both structured and unstructured data, and model training and deployment using advanced techniques in deep learning and transformers. Proficient in Python development, the candidate has successfully designed custom datasets, improved data acquisition pipelines, and presented project outcomes through effective storytelling methodologies, supplemented by an AWS Cloud Practitioner certification.

A skilled Data Scientist with substantial experience in Python programming, particularly utilizing libraries such as Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow, and Keras, alongside SQL and Power BI for data analysis and visualization. Proficient in data scraping automation and collaboration with global teams to resolve data-related client issues, having successfully led data science projects in the energy sector by employing the CRISP-DM framework and Agile methodologies. As an instructor, effectively conveyed foundational concepts of Python and machine learning, enhancing learners' understanding of regression, classification, clustering, and advanced ML techniques. Holds a specialization in Neural Networks from MIT and certifications in Python and SQL from Kaggle.

Possessing a strong foundation in Chemical Engineering and Computer Science, this professional has made significant contributions in the chemical industry as a laboratory and production intern, and as an innovation researcher focusing on Industry 4.0 technologies. Currently employed as a Data Scientist, expertise encompasses developing solutions in Data Science, Analytics, Machine Learning, and IoT. Proficient in statistical modeling, computer vision, and deep learning using Python-based frameworks and tools, with hands-on experience integrating edge devices and cloud services. Additionally, has demonstrated academic involvement through research initiatives and software development for educational purposes, further enhancing skills in advanced analytics and process control.

Data scientist with over two years of experience and a degree in Aeronautical Engineering, specializing in data engineering and data science projects. Expertise includes utilizing statistical analysis and machine learning methodologies to solve complex problems, with proficiency in tools such as Python, R, Power BI, and SQL. Recent accomplishments involve developing machine learning models for industrial applications, creating ETL tools for carbon emission reporting, and designing management dashboards to improve decision-making processes. Holds multiple certifications in Data Science and relevant technologies, demonstrating a commitment to continuous professional development.

A proficient backend Python developer with extensive expertise in software development across various domains, including RESTful API design, asynchronous programming, cloud deployment, natural language processing (NLP), and web scraping. This candidate's academic background in Mechatronics, Robotics, and Control Engineering, coupled with a passion for machine learning, deep learning, and computer vision, enhances their versatile skill set. Known for meticulous attention to detail, flexibility, and a steadfast commitment to quality, they actively pursue continuous learning and are adept at problem-solving, focusing on process optimization and improved outcomes. With a strong work ethic and intrinsic curiosity, this highly motivated individual seeks to leverage technology for positive global impact.

Possessing a postgraduate degree in Machine Learning and an undergraduate degree in Spanish Language Studies, this candidate aims to further their expertise in Natural Language Processing (NLP). They bring over a decade of experience as a language educator and have been actively engaged as a translator and interpreter since 2018, expressing a keen interest in expanding professional experience in the IT sector. With over two years of hands-on experience in Python and data preprocessing libraries for predictive models, including classical algorithms and Transformers, they hold a Professional Certificate as a TensorFlow Developer from DeepLearning.AI. Additionally, they have authored a published paper on models applied to the classification of Spanish dialects and are fluent in Portuguese and Spanish, with advanced proficiency in English.

A highly skilled data scientist and computer engineer with a Bachelor’s degree in Computer Engineering from Universidade de Araraquara, a Master’s in Computer Science and Computational Mathematics from the Instituto de Ciências Matemáticas e de Computação at USP, and a recent MBA in Data Science from USP/Esalq. Currently a doctoral candidate, engaged in advanced research focusing on machine learning applications for data quality assessment. Proven ability to apply theoretical knowledge to practical challenges, illustrated by substantial experience at Ford, where innovative facial recognition systems were developed utilizing advanced programming skills in Python and machine learning frameworks. Demonstrates strong analytical capabilities, collaborative spirit, and effective communication skills while mentoring MBA students.