Machine Learning Engineer and Ph.D. candidate in Computer Engineering. I have experience with ML/AI, Natural Language Processing, and Computer Vision in several domains, Remote sensing, distributed systems, and other stuff.Quick rundown:- Exhaustive experience in Natural Language Processing and Machine Learning in several domains - Data Science (Pandas, Numpy, Scikit-Learn, Matplotlib, Seaborn), Deep Learning and Artificial Intelligence (Keras, PyTorch, Fairseq) - NLP (NLTK, Transformers, Longchain, LLaMA and other LLMs) - MLOps (MLflow, DVC) - LLMs (RAG, Fine-tuning and Prompt Engineering)- Experient with remote sensing, land cover change, and satellite image processing using AI and statistical methods - Remote sensing (GDAL, Rasterio, GeoPandas, GEE) - Satellite (Sentinel, Landsat, MODIS, Planet)- Proficient at using and managing Unix-like systems: - Comfortable with common CLI tools, shell syntax/scripts/commands, SSH, rsync/scp and so on - Have some experience managing production servers (deploying updates, configuring reverse proxies, load balancers, databases, firewalls, etc)- Experient with best practices (proficient in version control with git, configuring and using static and dynamic code analysis tools, continuous integration, automated testing, etc)- Back-end development: - Back-end: Python (FastAPI and Flask), Node (Express) - Relational (SQlite and PostgreSQL) and non-relational databases (MongoDB, Redis), and ORMs (SQLAlchemy and Mongoose)- Container, virtualization and orchestration technologies (Docker, Kubernetes)- Microservice and distributed architectures, message brokers and queues (Redis, RabbitMQ)Contact me at any time!