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Senior ML Engineer & Applied Researcher | Industrial AI | Research-to-Production Systems | PhD in Computer Vision
Senior ML Engineer & Applied Researcher with 8+ years of experience industrializing AI/ML systems — from computer vision research to ML pipelines and platform tooling. I combine the rigor of a PhD in Computer Vision with hands-on AI systems engineering, bridging research experimentation and production deployment through ML workflows, model monitoring, and MLOps practices. My work focuses on real-world constraints such as noisy data, limited datasets, latency budgets, and long-term model reliability. Industrial AI Projects • Edge AI for Maritime Surveillance Designed edge-deployable ship detection models for satellite imagery using NAS, optimizing recall, latency, and FLOPs trade-offs. Implemented production drift monitoring for covariate and concept drift. • Industrial Operator Safety Monitoring Evaluated and deployed segmentation models including DFormerV2, SAM2, and MobileSAM for real-time operator detection in industrial risk zones. • Aerospace Electronics Defect Detection Developed a hybrid inspection pipeline combining U-Net segmentation with Procrustes-based geometric analysis for robust aerospace defect detection. AI Platform & Infrastructure At ActiveEon, I developed the AI/ML layer of the ProActive Orchestration platform, contributing 100+ customizable workflows for ML, AutoML, Drift Detection, and Model-as-a-Service applications. Also contributed to the Python SDK through the @task and @job decorator system for scalable ML workflow orchestration. Research & Publications Author of 4 peer-reviewed publications and speaker at ICPR, VISAPP, OW2con, SophiaConf, and WAICF. Research Interests Computer Vision · Applied AI Systems · Neural Architecture Search · Drift Detection · Deep Learning Tech Stack Python · PyTorch · ONNX · Triton · FastAPI · MLflow · Docker · AWS · Prometheus/Grafana Particularly interested in roles that bridge resear
CVC Research Lab
Doctoral Stage , Computer Vision and Pattern Recognition
January 1, 2014 – January 1, 2015
MIA Lab-University La Rochelle
Doctor of Philosophy (PhD) , Computer Vision and Pattern Recognition
January 1, 2013 – January 1, 2017
Event Participation
Visão Computacional
January 1, 2013 – January 1, 2015
Federal University of Bahia - UFBA
MSc Mechatronics Engineering, Computer Vision, Image Processing Nota (Mechatronics, Robotics, and Automation Engineering)
January 1, 2010 – January 1, 2012
AREA1 Engineering School
BSc Computer Engineering, Mobile Robotics
January 1, 2004 – January 1, 2009
ogre.run
AI Consultant
January 1, 2024 – December 1, 2024
United States · Remote
ActiveEon
Senior R&D Engineer
May 1, 2017 – June 1, 2025
Paris, Île-de-France, France
MIA Lab-University La Rochelle
Researcher Phd Candidate
September 1, 2013 – May 1, 2017
Greater La Rochelle Area
CTAI
TI Supervisor
April 1, 2011 – March 1, 2012
Federal University of Bahia
JCL Tecnologia
Software Consultant
December 1, 2010 – August 1, 2013
Greater Salvador
SEMGE
Software Developer
October 1, 2006 – March 1, 2010
LBPLibrary
January 1, 2014 – December 1, 2016
A Collection of LBP algorithms for background subtraction in videos. https://github.com/carolinepacheco/lbplibrary
CNC Pen Plotter
March 1, 2010 – June 1, 2010
This machine was build at Mechatronic Systems course of Master's program in Mechatronics Engineering at Polytechnique School - Federal University of Bahia (UFBA), Brazil. Additional information: http://bit.ly/i3rLIu
Robot RAVE
January 1, 2008 – January 1, 2009
A robot platform for research and development in mobile robotics using r/c car. Additional information: http://bit.ly/ft0tC9
Cultural Fit Analysis
The candidate's background, spanning academic research (PhD) and industrial R&D, indicates a strong fit for roles that require both theoretical depth and practical application. Their work on diverse projects, from academic research to industrial AI solutions and LLM development, demonstrates a broad interest and adaptability. The experience with open-source models and contributions to platform development suggests a collaborative mindset. The long tenure at ActiveEon (8+ years) indicates loyalty and commitment.
Soft Skills & Operational Fit
The candidate's experience at ActiveEon highlights strong problem-solving skills, particularly in designing complex AI/ML solutions for industrial clients under real-world constraints (e.g., edge computing, small datasets). Their role as an AI Consultant and Senior R&D Engineer suggests an ability to work autonomously and contribute to strategic technical direction. Mentoring experience indicates good interpersonal and leadership potential. The diverse project portfolio (robotics, CNC, LBP algorithms) suggests adaptability and a proactive learning attitude.