Machine Learning Internship
Engineering - Software Development
Who we are
At Criteo, we connect 1.5 billion active shoppers with the things they need and love. Our technology takes an algorithmic approach to predict what user we show an ad to, when, and for what products. Our dataset is about 50 petabytes in Hadoop (more than 120 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.
What is it like to work in our R&D
Most of all, we are creators. From designing ground-breaking products to finding unique ways to solve technical challenges at an exceptional scale, our tech teams work with state of the art methodologies to shape the future of advertising.
The Criteo AI Lab brings together researchers, machine learning engineers, and data scientists. Our mission is to develop advertising solutions that provide value to Internet users around the world. We do so by pushing state-of-the-art ML methodologies into our products to drive better performance, and act as center of Machine Learning research and engineering excellence.
What You’ll Do
- In a team of 5-7, you will be working closely with your mentor to drive your project, design and ensure best practices are applied. You can ask questions and participate in all knowledge sharing sessions/workshops, etc. You are encouraged to actively voice your ideas whilst learning how to build and ship quality code into production which will likely affect millions of users instantly.
- Identify key prediction/classification problems, devise solutions, build prototypes, and stay current on published state-of-the-art algorithms.
- Gather and mine large data sets for turning them into understandable and actionable insights to ensure Criteo remains one step ahead of competitive threats.
- You will develop high-performance algorithms for precision targeting, test and implement the algorithms in scalable, product-ready code.
What you will be working on
- Test other than logistic regression models for banner design optimization (GBDT, neural networks...) and investigate some feature engineering around color sets used in banners.
- Interpretability of ML models at scale.
- Implement and benchmark various deep architectures in TensorFlow for bidding predictive models and cross feature auto detection/encoding applied to non-deep models.
Who you are
- You are currently in your last year of Bsc/Msc degree in a quantitative field (Engineering, Mathematics, Statistics, Computer Science).
- Experience with traditional and modern statistical learning techniques and you are proficient at processing data.
- Implementation experience with high-level languages, such as Python, Scala, Java, C#.
- Ideally you are fluent in the core toolkit of Data Science.
- You love manipulating large-scale data sets, building data pipelines, descriptive and predictive modelling and Implementing visualizations, dashboards, and reports.
- Passion for code quality, you are curious and dynamic.
- Good communication skills in English.
Want to Know More?
•What does it feel like to be part of something big? Get a snapshot
•Get the story directly from our R&D engineers, check our Medium R&D blog
•Interested in discovering your Criteo community first? Let’s meet
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.
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