Camila Alves Dias

About

Senior Machine Learning Engineer with 6+ years of experience designing, training, and deploying scalable AI solutions across computer vision, fraud detection, digital health, and enterprise analytics. Deep expertise in Python, PyTorch, TensorFlow, OpenCV, feature engineering, MLOps, and cloud platforms including Azure, Databricks, and BigQuery. Strong track record of translating research into production-ready systems, with cross-functional collaboration across product, engineering, and research teams.

Experience

• AI R&D Specialist - Digital Health & Sleep Analysis · Samsung Brasil10-01-2025

  - Architected CNN- and RNN-based models for multi-class sleep stage classification using Python, TensorFlow/PyTorch, NumPy, and signal-processing workflows for large-scale physiological data. - Built end-to-end feature engineering pipelines for biometric data using Python, Pandas, NumPy, and preprocessing techniques, improving model robustness and production readiness. - Translated state-of-the-art research into model improvements through experimentation, evaluation, and iterative deep learning development in Jupyter-based workflows. - Collaborated with hardware, health research, and software teams to integrate ML solutions into Samsung health product workflows.

• Data Scientist - Fraud Detection & GenAI · Globo03-01-2024 – 09-30-2025

  - Developed and deployed supervised and unsupervised ML models for real-time fraud detection using Python, Scikit-learn, SQL, and large-scale event data pipelines. - Built ETL pipelines in BigQuery using SQL, Python, and GCP-based analytics workflows to process millions of daily events and support near-real-time decisions. - Developed GenAI assistants using OpenAI GPT-4 and Gemini APIs with LangChain and Salesforce integrations, automating customer service workflows. - Created dashboards in Looker Studio combining BigQuery, SQL, and business analytics reporting for marketing, operations, and IT teams.

• Machine Learning Engineer - MLOps & Big Data · ClearSale12-01-2022 – 10-31-2023

  - Built scalable PySpark pipelines for high-volume transaction data using Databricks, Spark, Python, and SQL, enabling real-time fraud scoring. - Migrated legacy SQL Server workflows to Databricks Feature Store using feature engineering and reusable ML pipeline design across production models. - Implemented CI/CD pipelines with Databricks, Azure, Azure DevOps, and MLflow, reducing deployment cycles from days to hours. - Established cloud-based model governance and auditability using Azure-based MLOps workflows for high-stakes machine learning systems.

• Computer Vision Engineer · PixForce04-01-2022 – 11-30-2022

  - Designed and implemented image segmentation pipelines using Python, OpenCV, PyTorch, and TensorFlow to isolate regions of interest and improve downstream analysis. - Developed object detection models for real-time image and video understanding using Python, OpenCV, YOLO-style architectures, and TensorFlow/PyTorch workflows. - Built image classification models for visual inspection and automated decision support using Python, OpenCV, TensorFlow, and PyTorch. - Worked on infrared and thermal image analysis models to estimate object temperature from visual data using Python, OpenCV, preprocessing pipelines, and deep learning regression/classification approaches. - Applied advanced preprocessing, error analysis, and statistical evaluation using Python, OpenCV, and experimental validation workflows to improve inference quality. - Collaborated with engineering and operations stakeholders to translate business requirements into deployable computer vision solutions.

• Backend Developer · Compass UOL03-01-2019 – 08-31-2019

  - Built BI dashboards and managed SQL databases using Power BI, Oracle SQL, Google Chat API, and Azure-based infrastructure for chatbot data workflows.

Education

• UnisinosPhD, Applied Computing (PhD, In Progress)
• Universidade Federal do Rio Grande (FURG)M.Sc., Computer Engineering
• Faculdades Integradas de CacoalB.Sc., Information Systems

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