Software Engineer in Machine Learning/


Your mission We are searching for great machine learning engineers to join the team responsible for: · Extending Criteo's large scale distributed machine learning library (e.g., implementing new distributed and scalable machine learning algorithms, improving their performance) · Building and improving prediction models for ad targeting; proving the business value of the changes and deploying them to production · Gathering and analyzing data, performing statistical modeling You'll have the opportunity to work on highly challenging problems with both engineering and scientific aspects; for example: · Click prediction:ÂHow do you accurately predict in less than a millisecond if the user will click on an ad? To qualify for this mission, you need: · MS degree in Computer Science or related quantitative field with 3 years of relevant experience or Ph.D degree in Computer Science or related quantitative field · Good understanding of the mathematical foundations behind machine learning algorithms · Great coding skills. Ability to write high performance production-grade code · Experience in one or more of the following areas: large-scale machine learning, recommender systems, or bandit algorithms ÂBonus points · Extensive experience in building and extending large scale production machine learning systems · Experience working with: Hadoop/Yarn, Spark · Experience in online advertising · Fluent in English About Criteo [CTRO] Criteo delivers personalized performance marketing at an extensive scale. A few figures: â 15 datacenters (8 with computing capacity 7 dedicated to network connectivity) Âacross US, EU, APAC â More than 15K servers, running a mix of Linux and Windows â One of the largest Hadoop clusters in Europe with close toÂ40PB of storage and 30.000 cores â â 30B HTTP requests and close to 3B unique banners displayed per day â Close to 1M HTTP requests per second handled during peak times â Â40Gbps of bandwidth, half of it through peering exchanges We recognize that engineering culture is key for building a world-class engineering organization.

Large-scale machine learning at Criteo


At Criteo, machine learning lies at the core of our business. We use machine learning for choosing when we want to display ads as well as for personalized product recommendations and for optimizing the look & feel of our banners (as we automatically generate our own banners for each partner using our catalog of products). Our motto at Criteo is "Performance is everything" and to deliver the best performance we can, we've built a large scale distributed machine learning framework, called Irma, that we use in production and for running experiments when we search for improvements on our models. In the past, performance advertising was all about predicting clicks. That was a while ago.