Daniel Lima

Background

About Daniel Lima

I am a Data Professional with over 10 years of experience, holding a Master's degree in Electrical Engineering with a focus on Machine Learning, and a Bachelor's in Computer Engineering. I'm passionate about solving complex problems with science and technology to drive meaningful, positive change. I believe empathy and knowledge are key values to creating impactful and sustainable solutions.Currently, I work as a Staff Machine Learning Engineer at BEES, where I lead the optimization of end-to-end training and deployment pipelines for computer vision models used in fraud detection, object detection, among other applications. My work spans from building production-grade architectures (EfficientNet, RT-DETR) using PyTorch and TensorFlow to implementing distributed training with DDP and Ray. I’ve driven major infrastructure and performance improvements, achieving up to 45× speed-ups in training time and reducing GPU memory usage by up to 50%.Throughout my career, I’ve designed and deployed data and machine learning pipelines for large-scale applications across industries such as retail, healthcare, finance, and manufacturing. I've led initiatives in cloud computing (AWS, GCP), data orchestration (Airflow), and cutting-edge GenAI solutions — including RAG systems and intelligent agents using Langchain and LangSmith.English Level: C2 (fluent in writing and speaking)Key Skills & TechnologiesMachine Learning & Deep Learning: Time Series Forecasting, Recommender Systems, Computer Vision, EfficientNet, RT-DETR, LightGBM, XGBoost, SARIMAX, CNNsGenAI & RAG Systems: Retrieval-Augmented Generation, Multimodal RAG, Langchain, LangGraph, AgentsMetaheuristics: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Cuckoo SearchData Engineering: ETL/ELT Pipelines, Data Lakes, Data Warehouses (Redshift, BigQuery), SQL, Data ModelingMLOps & Software Engineering: PyTorch, TensorFlow, MLflow, Airflow, Ray, DDP, Docker, Kubernetes, CI/CD, Jenkins, Flask, FastAPICloud Platforms: AWS (Glue, Lambda, S3, Redshift, EKS, EC2, AuroraDB), GCP (BigQuery), Azure DatabricksProgramming Languages: Python, PySpark, SQL, C#, C++, MatlabEngineering Best Practices: OOP, SOLID, Code Optimization, Unit & Integration TestingTools for Visualization & Collaboration: Tableau, Dash, Postman, Git ContactPhone:+55 91 98841-3504Email: daniel.vtlima@gmail.com