About Guillaume
Expert en algorithmique, data science et machine learning, avec une expérience académique (normalien, doctorat, CNRS) et industrielle (Criteo). Je propose des services d'analyse de données, de conseil, de développement et de formation. En combinant mon expertise technique et ma compréhension des enjeux commerciaux et industriels, je suis en mesure de vous accompagner dans la réalisation de vos projets. Voici quelques exemples de services :
- Analyse de données
- Etude et rapport des meilleures solutions existantes pour votre besoin en machine learning, IA et algorithmique
- Développement de POC et projets exploratoires, ainsi que leur mise en production
- Formation et conseil en machine learning, IA, algorithmique
N'hésitez pas à me contacter pour que l'on discute de vos projets et voir comment nous pouvons collaborer pour atteindre vos objectifs.
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- CriteoMachine Learning EngineerTECHSeptember 2021 - Today (4 years and 9 months)Paris, FranceMachine learning engineer in the product recommendation team at Criteo AI Lab. I was involved, among other things in:- developing large-scale recommendation systems with AI and deep embeddings, impacting billions of users,- analyzing large amounts of data, sometimes very noisy, including data from large-scale AB tests, to evaluate the quality and impact of new recommendation models before making deployment decisions, but also to improve models or isolate segments where models have a positive impact on business,- reading the literature and working closely with Criteo's research team to translate academic and theoretical models into testable models and put them into production,- supervising an intern working between the research team and the production team to put a recommendation model (based on a ranking and classification metric) into production,- giving lectures and tutorial sessions at Paris Dauphine in the master IASD, on vision learning and semantic search using embeddings and neural networks.
- Centre National de la Recherche ScientifiquePostdoctoral ResearcherSeptember 2019 - August 2021 (1 year and 11 months)Bordeaux, FranceTwo main topics:- DeepSynth CNRS project: program synthesis guided by machine learning. This led to an AAAI paper and we created an open source software which is available here: https://deepsynth.labri.fr/- Development of fast hierarchical clustering algorithms with approximation guarantees. This led to two ICML papers and the implementation of the algorithms in Cython.
- KTH Royal Institute of TechnologyPostdoctoral ResearcherSeptember 2018 - September 2019 (1 year)Stockholm, SwedenI worked on hardness of approximation of optimization problems. My research touched on topics such as sum-of-square algorithms, extremal set theory, the polynomial calculus proof system, and moderately exponential time algorithms for constraint satisfaction problems.
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Education
- Theoretical Computer ScienceEcole normale supérieure de Lyon2015Theoretical Computer Science
- Doctor of Philosophy - PhD, Computer ScienceUniversité Paris Diderot2018Doctor of Philosophy - PhD, Computer Science