Freelancer profile translated to English.

Description

Machine learning engineer for over 8 years, I can assist you with your machine learning and deep learning projects.

- Development and deployment of machine learning and deep learning models adapted to your needs

- Helping you develop your machine learning and data strategy (data management, training and deployment of machine learning/deep learning models, maintenance, cloud deployment, etc.)

- Deploying, maintaining, and updating your models in production on the back end, in the cloud, or internally (MLOps)

- Helping you define best practices for data management and software development around machine learning

I am a CentraleSupélec engineer specializing in machine learning. After completing and overseeing numerous data and research projects at Dreem, I participated in the development of key MLOps features at Dataiku, where AI is at the core of the product.

I enjoy both the research and development aspects of my profession. I want to support you rigorously and effectively in your projects.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris 1er Arrondissement (up to 15km)

Dataiku
Senior software engineer, MLOps
SOFTWARE PUBLISHING
June 2021 - Today (4 years and 11 months)
Paris, France
Actively worked on integration of the Dataiku platform (DSS) with MLflow open-source platform for external model import and experiment tracking
Lead the development of ML model export for scoring in python (dataiku-scoring)
Worked on integration with third parties cloud providers (AWS Sagemaker, Microsoft AzureML and Google vertex AI)
Python Angular MLflow Amazon Web Services (AWS) GCP MLOps
Dreem
Lead machine learning engineer (head of algorithms)
MEDICAL
October 2014 - April 2021 (6 years and 6 months)
Paris
Machine learning applied to sleep data (EEG, ECG time-series) for sleep stage detection, sleep apnea detection, sleep-related disorders
Lead several scientific publications on deep learning applied to sleep data
Lead validation of the performance of a sleep-recording product based on clinical trials and state-of-the-art deep learning algorithms
Deployed and maintained machine learning models back end side to perform scoring on data acquired with the product (MLops)
Deployed and maintain algorithm pipeline embedded in the product
Recruited and lead a team of five permanent data scientists and machine learning engineer
Deep Learning Machine learning Python Data science Pytorch Research Scientific Writing MLOps C/C++ Django