Senior Software Engineer - Machine Learning Team

Teads, The Global Media Platform, has an engineering team that brings together 200+ talented individuals in 3 main locations (Montpellier, Paris, and Bucharest). We are organized in agile and autonomous feature teams and core teams and share technical knowledge within several communities of practice.   To innovate, we promote diversity and are committed to creating an inclusive environment for all employees.   Our organization gives the possibility to work remotely part of the time and more flexibility is open to discussion. We also offer relocation packages if you prefer to settle down in one of our engineering offices.   👉  Join a team of passionate people who build quality and responsible advertising, at scale!     Our main Engineering matters

• Working on a very high traffic environment with low latency and high availability constraints
• Rich tech stack and system architecture to optimize for performance, scalability, resiliency and cost efficiency
• Fast changing environment where we continuously collaborate with Product teams and constantly adapt our Cloud infrastructure for new features and Products
• Management of large dataset with milliseconds order of magnitude access time to compute in near real time complex auction resolution algorithm
• Build efficient and easy to use web products used by thousands of users working for the world's most premium publishers, advertisers and agencies

  Our Machine Learning Team   The Machine Learning Team develops products to empower businesses to make data-driven decisions and optimize ML models performance. Notably, it is responsible for 3 tools:

• The A/B Test Framework is designed to facilitate controlled experiments for assessing the impact of changes in user experiences, features, or algorithms. It enables businesses to compare the performance of two or more variants (A and B) in a statistically rigorous manner.
• The Offline Experiments Framework is developed to allow data scientists and researchers to explore and iterate on machine learning models without directly impacting the live production environment.
• The Inference Engine for Production is a high-performance system designed to deploy and serve machine learning models at scale in production environments. It ensures low-latency and high-throughput predictions, allowing businesses to leverage models for real-time decision-making.

  What will you do?   As a Senior Software Engineer in our Machine Learning Team, 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.
• Create, design, develop, test and monitor your code in production autonomously and reliably.
• Implement ML algorithms and models end to end.
• Work together with the data scientists to improve our ML performance.
• Mentor other team members to improve their autonomy and Software Engineering skills.
• 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 latest Machine Learning technologies to make sure we constantly improve our ML system.

  What will you bring to the team?

• Good programming abilities. Testing your development is second nature to you, and you are very mindful about your application’s architecture, performance and maintainability and its overall quality.
• Multiple shipped projects in Software Engineering, and ideally in a ML context.
• Proficiency in Python is a plus.
• 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.

  Why work at Teads?  

At Teads, Product and Engineering work hand in hand and are aligned towards the same goal: to scale our business while continuing to create new and exciting products.

• We value team spirit, pragmatism, listening and we encourage initiatives.
• We promote end-to-end development: “You build it, you run it, you monitor it”.
• We share knowledge and su