HEADING:
Machine Learning and Computer Vision Engineer with 4+ years of production experience taking models from scratch to deployment across video analytics, affective computing, and digital health.
EXPERIENCE:
- Computer Vision and Video Analytics: Implemented models for multi-object tracking, 2D/3D pose estimation, gaze detection, and demographic classification for continuous camera monitoring. Built a deep learning model for visual attention distribution from scratch all the way to production API deployment.
- Camera-based Biometrics and Edge AI: Architected real-time pipelines extracting vital signs (HR, HRV, SpO2, respiration) and facial micro-expressions via rPPG from smartphone cameras, bridging models into a proprietary C++ core for mobile (iOS/Android).
- Applied AI and LLM Systems: Designed and deployed a clinical recommendation engine integrating multiple LLMs (OpenAI, Gemini, Groq, Ollama) on real-time patient data with automated evaluation and strict schema validation.
- Industrial Vision and Hardware: Architected modular CV systems managing multi-camera acquisition (Basler line-scan cameras) with hardware/software triggers and synchronized FIFO buffers for real-time anomaly detection.
- Research: Co-authored a peer-reviewed publication (Springer Cham, 2024) on acute pain intensity estimation using 17 Facial Action Units and head pose components under cross-dataset conditions.
rikya · · focus · HN ↗
REMOTE: Yes (Remote only)
WILLING TO RELOCATE: No
TECHNOLOGIES/SKILLS: Computer Vision, PyTorch, Python, OpenCV, C++, Deep Learning, Multi-Object Tracking, Pose/Gaze Estimation, MLOps, Docker, AWS, rPPG / Biosignals, LLM Orchestration
RÉSUMÉ/CV: Available on request
LINKEDIN: <a href="https://www.linkedin.com/in/federicapaoli" rel="nofollow">https://www.linkedin.com/in/federicapaoli
EMAIL: federicapaoli1@gmail.com
AVAILABLE FOR: B2B freelance/contract roles.
HEADING: Machine Learning and Computer Vision Engineer with 4+ years of production experience taking models from scratch to deployment across video analytics, affective computing, and digital health.
EXPERIENCE:
- Computer Vision and Video Analytics: Implemented models for multi-object tracking, 2D/3D pose estimation, gaze detection, and demographic classification for continuous camera monitoring. Built a deep learning model for visual attention distribution from scratch all the way to production API deployment.
- Camera-based Biometrics and Edge AI: Architected real-time pipelines extracting vital signs (HR, HRV, SpO2, respiration) and facial micro-expressions via rPPG from smartphone cameras, bridging models into a proprietary C++ core for mobile (iOS/Android).
- Applied AI and LLM Systems: Designed and deployed a clinical recommendation engine integrating multiple LLMs (OpenAI, Gemini, Groq, Ollama) on real-time patient data with automated evaluation and strict schema validation.
- Industrial Vision and Hardware: Architected modular CV systems managing multi-camera acquisition (Basler line-scan cameras) with hardware/software triggers and synchronized FIFO buffers for real-time anomaly detection.
- Research: Co-authored a peer-reviewed publication (Springer Cham, 2024) on acute pain intensity estimation using 17 Facial Action Units and head pose components under cross-dataset conditions.