À propos de Arij
Anglais
Bilingue ou natif
Français
Bilingue ou natif
Arabe
Bilingue ou natif
Coréen
Notions
Expériences
- CriteoMachine Learning EngineerE-COMMERCEjuin 2024 - Aujourd'hui (2 ans)Paris, France
- Fine-tuned an open-source LLM to perform structured attribute extraction, intent classification, and taxonomy enrichment at inference time, replacing paid APIs and delivering significant cost savings while maintaining data quality for downstream embedding training.
- Designed and deployed a large-scale offline data curation pipeline for foundation-model training: enriched product data via the fine tuned LLM before embedding creation, improving semantic consistency and retrieval performance.
- Fine-tuned large-scale multimodal embedding models serving mainly two downstream consumers: (1) an agentic ads-in-chat product (ChatGPT-style) requiring high-precision semantic retrieval, and (2) a recommendation system using FAISS, k-NN, and Elasticsearch for large-scale product ranking.
- Served as technical interface with external partners (e.g., Anyscale), contributing to architectural decisions, production-readiness reviews, and distributed training best practices.
- Ran privacy audits on Criteo models to ensure no data was leaked during training,
- CriteoSoftware Development Engineerjanvier 2023 - juin 2024 (1 an et 5 mois)Paris, France
- Developed data ingestion workflows processing millions of first-party identifiers to power Criteo's large-scale user graph.
- Built the internal Opt-Out API, enabling compliant identifier removal across distributed ID-mapping systems, ensuring GDPR alignment.
- Maintained and optimized the ID Collection library, improving hashing, normalization, and consistency of identifiers (email, CRM IDs) across privacy-critical pipelines.
- Worked closely with Privacy and Platform teams to adapt data flows to evolving regulatory and experimentation constraints.
- IvaluaSoftware Development Engineerseptembre 2020 - janvier 2023 (2 ans et 4 mois)Paris, France
- Refactored a decade-old core service in the Procure-to-Pay product, boosting performance by 20%.
- Delivered new backend features in agile sprints with cross-functional teams.
- Identified and patched multiple XSS vulnerabilities, improving product security posture.
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Formations
- Masters degree in Data scienceUniversité Paris Dauphine2020