Freelancer profile translated to English.

Description

I design and structure robust, scalable, and truly production-ready Machine Learning systems. My expertise covers the entire value chain: data quality, analysis of existing architectures, integration of ML/AI pipelines, and implementation of monitoring tools (monitoring, benchmarks, metrics) for informed decision-making. At the interface between technical teams and decision-makers, I transform strategic objectives into concrete, prioritized, and iterative technical plans.

My approach combines theoretical rigor with field experience, specializing in embedded AI and audio/image processing for environments with strict latency or computational constraints.

Industry field of expertise

Languages

French
Native or bilingual
Spanish
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

Orosound,
Audio Signal Processing & Machine Learning Engineer
TECH
January 2023 - January 2025 (2 years)
Paris, France
Design, testing, and integration of AI models for noise reduction and voice enhancement on audio headsets and earbuds, with very low latency and low power constraints.
Creation of a Python/C integration framework that drastically increased iteration speed and problem-solving capacity for clients.
AI and data analysis Machine learning Python C/C++
SoundHound
Audio Signal Processing & Machine Learning Engineer
TECH
February 2021 - June 2023 (2 years and 4 months)
Paris, France
Training and auditing of Deep Learning models for speech recognition, using audio signal processing algorithms for training data preparation and augmentation, benchmark development, and model analysis.
Complete restructuring of the training system to simplify usage and improve modularity, reducing integration time for new features.
Machine learning Pytorch AI and data analysis Python TensorFlow
CNMAT, UC Berkeley
Machine Learning Research Assistant
TECH
October 2020 - January 2021 (3 months)
Berkeley, United States
Design of an instrument classifier based on a CNN and RNN architecture; published at AI Music Creativity 2020.
Machine learning