Senior ML Engineer — Scale Real-Time Ads (Hybrid)

Criteo; Paris; Hybride; EUR 90 000 - 120 000; Plein temps

Avantages offerts par ce poste

Hybrid work model

Learning & career development programs

Health benefits

Résumé du poste

Criteo’s AI Lab is hiring Machine Learning Engineers to design and deploy the next generation of AI-powered advertising. You’ll work with researchers, engineers, and data scientists on production systems handling petabytes of data and real-time decisions.

You will experiment, iterate, and collaborate across teams to turn research ideas into scalable solutions, balancing scientific exploration with measurable business impact.

Qualifications

• Strong foundations in Machine Learning, Deep Learning, Statistics, or Applied Mathematics.
• Experience building, training, and evaluating deep learning models in production environments.
• Familiarity with Transformer-based models, representation learning, or recommender systems.
• Proficiency in Python and PyTorch.
• Experience with large-scale datasets and distributed training environments.
• Strong experimental mindset focused on measurable outcomes.
• Ability to collaborate across research and engineering teams.

Responsabilités

• Design, develop, and evaluate novel ML approaches for prediction, optimization, and recommendation.
• Transform research ideas into production systems handling petabytes of data and real-time decisions.
• Collaborate with researchers, software engineers, product managers, and data scientists to ship solutions.
• Experiment, iterate, and validate through offline evaluations and online A/B tests.
• Contribute to a culture of technical excellence and knowledge sharing.

Connaissances

Machine Learning

Deep Learning

Statistics

Applied Mathematics

Python

PyTorch

Distributed Training

Experimentation mindset

Collaboration

Outils

GPU Computing

MLOps

A/B testing frameworks

Description du poste

Criteo’s AI Lab is hiring Machine Learning Engineers to design and deploy the next generation of AI-powered advertising. You’ll work with researchers, engineers, and data scientists on production systems handling petabytes of data and real-time decisions.

You will experiment, iterate, and collaborate across teams to turn research ideas into scalable solutions, balancing scientific exploration with measurable business impact.