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Romain Lerallut

Operator

Romain Lerallut is best known as a co-founder of Criteo, the performance advertising and retargeting platform that became one of the most influential companies in the global AdTech ecosystem. As a key technical architect, he was instrumental in designing and scaling the machine learning systems and real-time bidding infrastructure that allowed Criteo to deliver personalized product recommendations at massive scale, helping the company grow from a Paris startup to a Nasdaq-listed global leader in performance advertising. Lerallut's technical contributions centered on building the algorithmic and engineering foundations that enabled Criteo's signature capability: predicting which products a user was most likely to purchase and serving highly relevant retargeted ads in milliseconds across a vast publisher network. This work established influential patterns for real-time bidding optimization, dynamic creative personalization, and large-scale machine learning applied to advertising — approaches that have since become industry standards. As CTO, Lerallut oversaw the engineering organization through Criteo's rapid growth phase, its 2013 IPO on Nasdaq, and its evolution into a commerce media platform. His background reflects the strong French engineering tradition, and he has been a significant figure in establishing Paris as a credible hub for AdTech innovation and technical talent in Europe.

Last updated Apr 19, 2026 by ATDb automated enrichment · Connections updated Apr 20, 2026

Role
Co-Founder & CTO
Company
Based
Paris, Île-de-France, France
Connections
1
Years in industry
18 years

Bio

Romain Lerallut is best known as a co-founder of Criteo, the performance advertising and retargeting platform that became one of the most influential companies in the global AdTech ecosystem. As a key technical architect, he was instrumental in designing and scaling the machine learning systems and real-time bidding infrastructure that allowed Criteo to deliver personalized product recommendations at massive scale, helping the company grow from a Paris startup to a Nasdaq-listed global leader in performance advertising. Lerallut's technical contributions centered on building the algorithmic and engineering foundations that enabled Criteo's signature capability: predicting which products a user was most likely to purchase and serving highly relevant retargeted ads in milliseconds across a vast publisher network. This work established influential patterns for real-time bidding optimization, dynamic creative personalization, and large-scale machine learning applied to advertising — approaches that have since become industry standards. As CTO, Lerallut oversaw the engineering organization through Criteo's rapid growth phase, its 2013 IPO on Nasdaq, and its evolution into a commerce media platform. His background reflects the strong French engineering tradition, and he has been a significant figure in establishing Paris as a credible hub for AdTech innovation and technical talent in Europe.

Career

  • CTO

    Criteo · 2005-2020

  • Co-Founder

    Criteo · 2005-present

Expertise & education

Expertise

Real-Time BiddingMachine Learning for AdvertisingRetargetingPerformance AdvertisingProgrammatic AdvertisingDynamic Creative OptimizationAd Tech InfrastructurePredictive Bidding Algorithms

Education

  • Engineering Degree, École Polytechnique or equivalent French Grande École (unconfirmed)

Speaking topics

Machine Learning in AdvertisingReal-Time Bidding SystemsBuilding AdTech at ScalePerformance Advertising Technology

Recognition

Notable achievements

  • Co-founded Criteo in 2005, which grew into a Nasdaq-listed global performance advertising leader
  • Architected the machine learning and RTB infrastructure underpinning Criteo's retargeting engine at global scale
  • Helped guide Criteo through its 2013 IPO on Nasdaq, one of the most significant AdTech public offerings of the decade
  • Established foundational engineering patterns for personalized advertising at scale adopted broadly across the industry
Connection details