Who we are
At Criteo, we connect 1.2 billion active shoppers with the things they need and love. Our technology takes an algorithmic approach to determining what user we show an ad to, when, and for what products. Our dataset is about 45 petabytes in Hadoop (more than 90 TB extra per day) and we take less than 10ms to respond to an ad request. This is truly big data and machine learning without the buzzwords. If scale and complexity excite you, join us.
Criteo AI Lab is pioneering innovations in online publishing and advertising. As the center of scientific excellence in the company, Criteo AI Lab in Grenoble, Paris, Palo Alto deliver both fundamental and applied scientific leadership through published research, product innovations and new technologies powering the company's products.
We are looking for outstanding machine learning research scientists whose skills span the entire spectrum of scientific research, i.e. data gathering/cleaning, modeling, implementation, publication and presentation.
Samplings of Research Topics
- Click prediction How do you accurately predict if the user will click on an ad in less than a millisecond? Thankfully, you have billions of data points to help you.
- Recommender systems A standard SVD works well. But what happens when you have to choose the top products amongst hundreds of thousands for every user, 2 billion times per day, in less than 50ms?
- Auction theory In a second-price auction, the theoretical optimal is to bid the expected value. But what happens when you run 15 billion auctions per day against the same competitors?
- Explore/exploit It's easy, UCB and Thomson sampling have low regret. But what happens when new products come and go and when each ad displayed changes the reward of each arm?
- Game theory/Reinforcement learning How to find the optimal bidding strategy across multiple auctions? Can this be cast as a reinforcement learning problem in very high dimensions with unpredictable rewards.
- Offline testing/Metrics You can always compute the classification error on model predicting the probability of a click. But is this really related to the online performance of a new model? What is the right offline metric that predicts online performance?
- Optimization Stochastic gradient descent is great when you have lots of data. But what do you do when all data are not equal and you must distribute the learning over several hundred nodes?
What you'll do
- Understand and shape the product direction by contributing innovative ideas, specifically as a result of data mining and experimental data modeling
- Influence the strategic vision for the research team and Criteo at large.
- Identify new research opportunities at Criteo and lead the exploration of these ideas and pursue patents/publications where appropriate.
- Interact with other teams to define interfaces and understand and resolve dependencies
- 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.
- Mentor team members, oversee the creation of technical documents and work towards establishing Criteo as a center of excellence in computational advertising.
Who you are
- PhD in Machine Learning or a related field along with at least five years of experience.
- Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data.
- Strong implementation experience with languages, such as Python, Perl, Ruby, Java, C#, Scala etc.
- Familiarity with Linux/Unix/Shell environments.
- Knowledge of Hadoop programming environments (e.g. Pig, Hive).
- Excellent track record in conducting and reporting results of original and collaborative research with publications.
- Prior experience in optimization of online advertising is a plus.
At Criteo, we dare to be different. We believe that diversity fuels innovation and creates an energy that can be seen and felt all over Criteo. We champion different perspectives and are committed to creating a workplace where all Criteos are heard, feel a sense of belonging, and are treated with respect and dignity.
Criteo collects your personal data for the purposes of managing Criteo's recruitment related activities. Consequently, Criteo may use your personal data in relation to the evaluation and selection of applicants. Your information will be accessible to the different Criteo entities across the world. By clicking the "Apply" button you expressly give your consent.