Software & ML Engineer


Paris, France

May 2022 - now

  • Python code refactoring
  • Migration from Flask app to Celery app with Redis backend
  • Implementation integration tests (Docker Compose, MinIO, Pytest, Celery, Redis) running in Github worflow
  • Migration from Kubernetes on Google Cloud Platform to Serverless + S3 + Cloudfront + Terraform on AWS
  • Implementation of a simple authentication feature using Lambda Authorizer, DynamoDB and Basic Auth.
  • Development of a slack bot to validate images generated by a ML pipeline
  • Deployment of a Triton Inference Server on AWS Sagemaker Multi-Model Endpoint with Terraform and a Gradio interface with the Serverless Framework

Machine Learning Engineer & Co-Founder of Sievable

Inria Startup Studio

Paris, France

July 2020 - May 2022

  • Joined Inria Startup Studio and received 1 year of funding to develop Sievable, a collaborative filter-based search engine powered by machine learning.

Machine Learning Engineer Intern


Cambridge, UK

Mars 2020 - May 2020

  • Research on generative neural networks for speech synthesis.
  • Developed a Python library to estimate ML pipelines performances on ARM processors.

Machine Learning Researcher Intern

CNRS (National Centre For Scientific Research)

Toulouse, France

Apr. 2019 - Sep. 2019

  • Developed a small Python library based on PyTorch to build Convolutional Spiking Neural Networks and train them using surrogate gradient methods.
  • Showed that "Integrate and Fire" neurons with lateral connections can be used to implement a multidimensional "Send on Delta" sampling scheme.