ML Engineer

We are looking for a ML Engineer to work closely with the ML Architect to develop on ML frameworks (TensorFlow, Scikit-Learn, Pytorch), Experimentation platform and tools. This role has the responsabilities to: Develop large-scale distributed machine learning systems that are scalable, performant, efficient, and reliable Collaborating with cross-functional teams to help deploy/integrate machine learning models. Liaise with the BUs for their ML needs and work on the cross-BU ML portfolio. Optimize feature extraction, transformation and selection. Work with and manage. Feature Stores for reusability across ML pipelines. Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities Requirements 5+ years of experience as a Machine Learning Engineer. Strong experience with supervised and unsupervised learning, survival analysis, time series modeling, and statistical forecasting. Skilled in building predictive models (e.g. churn, user journey, sales forecasting) using behavioral data. Proficient with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn. Experienced in model training, versioning, and monitoring. Solid background in MLOps practices: CI/CD, Docker, Kubernetes, Airflow, SageMaker, MLflow, model observability tools, and feature stores.