Joao Vicente

Machine Learning Engineer @ Solinftec

About

Work experience with projects, data science and machine learning: - Work experience creating machine learning models to solve NLP problems; - Work experience creating deep learning models to solve computer vision problems; - Work experience implementing APIs at the cloud (AWS); - Solid knowledge in programming (python); - Bachelor in Computer Engineer. Since 2020, I have immersed myself in software and machine learning development, which catalyzed positive impacts on Pantanal's biodiversity, government revenue growth and global agriculture. Motivated by delivering quality solutions with great impact. I am curious, adaptable and easygoing. I am always open to new challenges.

Country

Brazil

City

São Paulo

Industry

Information Technology & Services

Skill

Large Language Models (LLM), FastAPI, Natural Language Processing (NLP), C++, OpenCV, Golang, Go (Programming Language), Spring Boot, Artificial Intelligence (AI), Redis, TypeScript, React.js, Node.js, Data Visualization, Keras, Data Science, TensorFlow, C (Programming Language), Java, Calculus

Experience

Machine Learning Engineer

Solinftec

2023-12 - Present · 2 yrs 10 mos

Brazil

- I work with chatbot development with LLMs, developing the main functionalities, making technical decisions, architecting the projects and helping the team. - Backend integration with external LLM APIs (openAI) and other NLP models (zero-shot, Sentence Transformers, NER, etc). - Creation and maintenance of vector databases for RAG in texts. Stack: Python, FastAPI, OpenAI, Qdrant, Docker, AWS, Pytorch and Transformers.

Machine Learning Engineer

AZ Tecnologia em Gestão

2022-1 - 2023-9 · 1 yr 9 mos

Campo Grande, Mato Grosso do Sul, Brazil

- SQL queries, data processing, exploratory analysis and data visualization. - NLP tools and techniques (preprocessing, regEx, tokenizers, TF-IDF, n-grams, skip-gram, embeddings, clustering, classification, etc). - Training and deployment of Machine Learning models (BERT, logistic regression, XGboost, etc). - Development of Neural Networks to predict divergences in trajectories. Stack: Python, Flask, FastAPI, Pandas, Matplotlib, Scikit-Learn, NumPy, Pytorch, TensorFlow and Transformers. Redis, SQL server, Linux, docker-compose.

Deep Learning Researcher

Artificial Intelligence Laboratory (UFMS)

2020-7 - 2021-12 · 1 yr 6 mos

Campo Grande, Mato Grosso do Sul, Brazil

- Development of deep learning models for detection and classification of jaguars. - Computer vision tools and techniques: convolution, normalization, cross-validation, accuracy, AUC, confusion-matrix, etc. Stack: Python, Linux, python virtualenv, docker.