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.