Research Intern

What You'll Do:

The Criteo AI Lab is pioneering innovations in computational advertising. As the center of scientific excellence in the company, we deliver both fundamental and applied scientific leadership through published research, product innovations and new technologies powering the company's products.

The Criteo AI Lab operates within the spectrum of two main roles: applied research and fundamental research. In the context of academic contributions, Research Scientists at Criteo are encouraged and fully-supported to publish their works at international conferences, collaborate with academic partners, file for patents, release datasets and help establish the state-of-art in computational advertising. Part of their role is to

* Identify new research opportunities at Criteo and lead the exploration of these ideas and pursue patents/publications where appropriate. Current interests are related to generative AI, foundation models, Generative Information Retrieval, trustworthiness in Generative Modelling, alignementreasoning and planning in LLM-based agents.

* Maintain world-class academic credentials through publications, presentations, external collaborations and service to the research community.

* Develop high-performance algorithms, test and implement the algorithms in scalable and product-ready code.

* Understand and shape the product direction by contributing innovative ideas.

Academic Research Proposed Topics: More specifically, the current topics are open

* Generative Video Modelling with Variational state-space models

* Foundation models for user behaviour prediction

* Bias in Generative model: Sampling low-density regions

* Discrete Generative models based on Flow matching

Who You Are:

• You are currently in your last year of Msc degree in a quantitative field (Engineering, Mathematics, Statistics, Computer Science) in a French school or university able to provide an internship agreement.
• Strong background in machine learning and statistics. Most positions require familiarity with deep learning architectures, such as transformers or state-space models as well as strong technical knowledge on generative modelling (GANs, Diffusion models and Flow Matching)
• Implementation experience with high-level languages, such as Python. Most positions require experience with deep learning frameworks (PyTorch or JAX).
• Good communication skills in English.

We acknowledge that many candidates may not meet every single role requirement listed above. If your experience looks a little different from our requirements but you believe that you can still bring value to the role, we’d love to see your application!​

Who We Are:

What We Offer: