We are looking for a Machine Learning Software Engineer to work on our Advertising Platform, reaching 1.7Bn users per month.
Our engineering team brings together 150+ talented individuals in 3 main locations (Montpellier, Paris, and Bucharest). We are organized in agile and autonomous feature teams and we also share technical knowledge within several communities of practice.
Our main engineering challenges:
- We work in a very high traffic environment with low latency constraints
- Web and mobile complexity, we are trying to offer a similar user experience on a wide range of contexts (device, OS, browser, etc.)
- An infinite source of Machine Learning use cases, ranging from ad performance prediction to ad delivery pacing and forecasting
- Large datasets that we need to compute in near real time (auction resolution) and even greater volumes for analytics use cases
- We operate globally and constantly think about new products to build the future of the media
As a Machine Learning Software Engineer, your missions will be to:
- Improve existing ML library & tools allowing to explore and analyze more and more data and provide accurate feedback on the Teads activities.
- Develop new algorithms & new approaches to provide accurate predictions and drive new products.
- Implement ML algorithms and models end to end.
- Work together with the data scientists to improve our ML performance.
- Collaborate with a variety of teams to develop services from design to production.
- Make sure the software is in good hands by writing, running and automating tests (unit, functional, load…).
- Keep up to date with the latests Machine Learning technologies to make sure we always use the best class algorithms according to the context
Your skills and experiences:
- Good experience in software engineering with a focus on Quality (testing, maintainability, performance…).
- Strong problem solving skills.
- Strong communication skills both written and oral, and a great team spirit.
- Working collaboratively with the team, able to explain your decision and share your knowledge.
- Good understanding of Machine Learning concepts and algorithms.
- Experience working with the whole lifecycle of machine learning models, from design to deploy.
- Large-scale distributed systems, Service Oriented Architecture
- Previous experience with all or some of the elements of our Stack (we mainly use Scala, Spark, Breeze, Kafka, AWS, Jupyter notebooks)
- Knowledge of the JVM (GC, Concurrency…)
- Experience in high performance and/or low latency systems
- SQL and NoSQL datastores
- Experience with machine learning frameworks (mllib, sklearn, numpy, tensorflow, pytorch etc.)
If you want to apply machine learning at scale and solve high scalability problems, join us, we provide competitive benefits and in-house training!
Teads, The Global Media Platform, is the single access point for advertisers to connect to the world’s best publishers and reach an audience of over 1.7 billion people every month.
Teads’ made-for-mobile ad experiences deliver the best combination of mass reach and brand safety in the market. Teads’ end-to-end platform provides a sustainable advertising ecosystem that respectfully connects brands to consumers. Teads demand-side, sell-side and creative technology delivers effective and engaging advertising experiences for consumers, guaranteed outcomes for brands, and ultimately powers publishers with better monetization solutions to fund quality journalism.
Teads partners with the leading marketers, agencies and publishers through a team of 850 people in 29 countries.
We're committed to creating a dynamic work environment that values diversity and inclusion, and represents employees across a variety of skill sets. We embrace contributions from all ages, sexes, races, ethnicities, religions, sexual orientations and gender identities.