Senior Machine Learning Engineer

Our commitment to innovation and excellence has driven us to seek out the best talent to help us build the future. We’re building up a multidisciplinary HQ AI Programs team, dedicated to supporting corporate functions and Global Publishing departments in the implementation of ambitious AI projects.

In that context, we’re looking for a Senior Machine Learning Engineer. The archetypal mission for this position would be to:

• Stay up to date with the research literature
• Translate research papers into operational code, implementing them from scratch and customizing them when needed
• Write, optimize, and produce high quality code that can run at scale, using modern best practices, sharing back to the open-source community when possible
• Ship models or prediction pipelines to production in our internal or public cloud infrastructure

Key Responsibilities

• Taking ownership over the projects you build and pushing them ahead, with a strong autonomy and creativity, keeping in mind the constraints of production environments.
• Experiment with a “try hard, fail fast” mindset: Research is evolving fast, and no one can know all the subfields of Machine Learning by heart. But we are never afraid to throw a punch at a new paper or an open-source repository with messy code, and so shouldn’t you be.
• Develop and maintain scalable machine learning pipelines and infrastructure.
• Monitor and evaluate the performance of deployed models, ensuring accuracy and efficiency.

Requirements

Qualifications

• Strong experience in machine learning engineering or a related field, with proven track record of deploying machine learning models in production environments.
• Strong programming skills – Python of course, but experience with a lower-level language would be a big plus – and a keen passion for coding.
• Extensive experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Understanding of microservice-based architectures. Experience with REST APIs and models deployment to production using Kubernetes in the cloud would be a big plus.
• Strong communication skills – English mandatory.