Adevinta is a marketplace specialist, operating digital marketplaces in 16 countries in Europe, Latin America and North Africa.
Our leading local brands include Leboncoin in France, InfoJobs in Spain, Subito in Italy, Jofogás in Hungary, and Segundamano in Mexico, among many others.
Adevintas local marketplaces thrive through global connections and networks of knowledge.
Our brands are supported by tech hubs in Paris and Barcelona. Their goal is to develop common global product & innovation platforms which all of our brands can leverage;
creating data and identity based ecosystems; empowering local entrepreneurs, delighting users, and helping us achieve our mission of creating perfect matches on the world's most trusted marketplaces.
Search Engineering is a new team comprised of highly skilled and senior engineers; experts in the search domain. We are building a global Search Component in our Paris Hub which we will quickly take on a journey from MVP to 100 +million unique users a month as we integrate the product with our marketplaces all over the world.
Our teams very autonomous and self organising; they are empowered to define the stack, approach to agile and architecture as a collective rather than from the top down.
Selection of the right machine learning algorithm for business goals
Build scalable machine learning tools, distributed clusters and models for search (MLR)
Experiment with different models and assess their potential in offline evaluations and by setting up A / B tests
Collaborate in cross-functional teams consisting of product managers, data engineers and analysts to build a great search product that correspond to the needs of our market places
Contribute to the end-to-end deployment of machine learning models
Popularize search initiatives via Medium posts and meetup talks and our internal community
PhD or Masters degree (or equivalent) in computer science / mathematics / physics or a relevant scientific field
Engineer by heart, but passionate about machine learning
Experience with large data sets, distributed computing, and Apache Spark or Hadoop / MapReduce is a plus.
Experience with streaming tools such as Kafka, Spark Streaming, Flink is a plus.
Experience with AWS and / or other cloud providers is a plus
Being able to communicate your findings in a concise way to a technical and non-technical audience
Comfortable working in an iterative incremental framework
Exposure to Search technologies like Lucene, Solr and Elastic Search
Knowledge in Machine Learning, Natural Language Processing and statistical techniques such as query expansions for search