About Romain
Machine Learning Engineer with data engineering and analytics skills.
I'm specialised in analytics for unstructured data. I can help you make sense of your unstructured data (user feedback / reviews, CX tickets, surveys, ...) and correlate it with product and business metrics.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- Too Good To GoMachine Learning EngineerAGRICULTUREDecember 2022 - Today (3 years and 6 months)First ML Engineer hired to design and build a discount optimisation system from scratch to help retailers reduce waste and increase profits.Including:- Setting up and maintaining data pipelines (DBT, Snowflake)- Developing ML models to predict discount elasticity- Developing an optimisation system to decide which discount to apply and when- Developing and maintaining ML pipelines (Metaflow)- Working with other teams to improve data quality and availability- Developing a small experimentation framework and running AB tests in stores- Working closely with our PM to improve the product
- YokaiMLOpsTECHAugust 2022 - Today (3 years and 10 months)Paris, France- Python code refactoring- Migration from Flask app to Celery app with Redis backend- Implementation of 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.Yokai.ai:
- Python code refactoring
- Migration from Flask app to Celery app with Redis backend
- Integration tests (Docker Compose, MinIO, Pytest, Celery,
Redis) running in Github worflow- Migration from Kubernetes on Google Cloud Platform to Serverless
- Simple authentication feature using Lambda Authorizer,
DynamoDB and Basic Auth.- Development of a Slack bot to validate ML generated images
- Deployment of a Triton Inference Server on AWS Sagemaker Multi-Model Endpoint with Terraform and a Gradio interface with the Serverless Framework
- SievableCo-FounderSOFTWARE PUBLISHINGJuly 2020 - April 2022 (1 year and 9 months)Paris, FranceBuilding a collaborative filter-based search engine powered by machine learning, including:- joined Inria's Startup Studio with 1 year of funding- training of a neural network to predict whether a natural language filter matches an item description or not- design of a scalable search engine system with search result candidates selection using clustering- designed a custom MLOps pipeline to automatically pull our datasets from different sources, train our model, update our items embeddings and deploy everything- developed our own search engine platform allowing users to search, index new content and contribute by annotating data- created our own cryptocurrency on the Solana blockchain to reward contributorsUsing: PyTorch, FAISS, MySQL, Redis, GraphQL, React, Solana Javascript API, RabbitMQ, Terraform, Docker, Kubernetes, Cloudflare Deployed on Scaleway.
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Education
- Master of ScienceÉcole normale supérieure Paris-Saclay2019Master of Science - MS, Mathematics
- Master of ScienceTélécom Paris2018Master of Science - MS