À propos de Alaa
ML Engineer depuis 4 ans au sein d'une start-up qui a réalisé un exit réussi, j'ai participé à la croissance de son équipe data et d’implémenter plusieurs services “from scratch”, en faisant preuve d’initiative, autonomie, et adaptabilité.
J’ai acquis et partagé des connaissances et best practices, que je continue à développer
aujourd’hui autour de projets data afin de maximiser la valeur ajoutée business.
Français
Bilingue ou natif
Anglais
Bilingue ou natif
Arabe
Bilingue ou natif
Espagnol
Capacité professionnelle limitée
Accepte de travailler sur site
Paris (jusqu’à 15 km)
Expériences
- DiliTrustSenior ML EngineerHIGH TECHmars 2019 - mars 2023 (4 ans)Paris, France■ Contribute to defining mid / long term strategic ML objectives in close collaboration with the Product team■ Share best practices and processes■ Promote sustainable and scalable growth■ Build End to End NLP pipelines for legal document analysis, leveraging state of the art language modeling architectures■ Deploy services / workloads on a Kubernetes cluster using Terraform scripts (Infrastructure as a code)■ Contribute to code maintenance, testing and integration.■ Serve embeddings models using Flask / Gunicorn to speed uploading time during inference■ Extract, clean, export and maintain the ML Datalake (GCS)■ Export GCP Logs to a BigQuery Dataset, via Log Routers(terraform), and create Grafana dashboards for analysis■ Benchmarked and implemented SOTA contextualized textual embeddings■ Parallelized existing parts of code using native python and Dask■ Designed, trained and deployed a signature detection model
- Algorithmic crypto trading botML EngineerHIGH TECHjanvier 2021 - Aujourd'hui (5 ans et 5 mois)Paris, France■ Implemented and dockerized from scratch a crypto trading bot, including backtesting engine and exchange handler■ Implemented a real-time slack bot for remote control■ Implemented a reactive dashboard to evaluate / monitorstrategy performances
- ConfidentialFreelance ML EngineerCOMMERCE DE DÉTAILnovembre 2019 - janvier 2020 (2 mois)Paris, France■ Loaded and processed, in a distributed fashion, a large dataset of patents (500GB + in relational tables) into Parquet format■ Hierarchical Feature engineering■ Classified, in parallel, each patent by its IPC (international patentclassification) on a GCP
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Formations
- Master of ScienceEURECOM2019Data Science, Machine/Deep Learning, Statistical inference, Image processing, Text mining, NLP, Big Data.
- Engineer's Degree, IT & CommunicationSUP'COM2018Engineer's Degree, IT & Communication