Sr machine learning engineer - Rabat

Model Design and Development:

Design, train, and optimize Machine Learning and Deep Learning models using frameworks such as TensorFlow, PyTorch, and Scikit-learn. Collaborate with Data Scientists to turn prototypes into production-ready solutions.

Industrialization and Deployment:

Implement CI/CD pipelines for training, evaluation, and deployment of models on Azure. Automate these processes to ensure continuous, reliable delivery.

Performance Optimization in Production:

Improve model inference performance, reduce latency, and optimize costs. Make adjustments to ensure scalability and robustness.

MLOps and Cloud Architecture:

Contribute to building a comprehensive MLOps architecture, including versioning data and models, model registry, monitoring, and incident management.

Documentation and Best Practices:

Document models, pipelines, and processes to ensure maintainability, reusability, and compliance with company standards.

Collaboration and Communication:

Work closely with Data Science, Data Engineering, and DevOps teams in an agile, multicultural environment to deliver high-value solutions.
Minimum of 5 years in Machine Learning, Data Engineering, or related fields Proven experience in end-to-end model deployment, monitoring, and maintenance in production Cloud experience, ideally with Azure, for implementing MLOps solutions

Technical Skills Required:

Programming Languages: Python, SQL, PySpark ML Frameworks and Tools: TensorFlow, PyTorch, Scikit-learn, MLflow, Kubeflow Cloud Platforms: Azure (Azure ML, AKS, Data Lake, Data Factory, Databricks) DevOps & Automation: Docker, GitHub Actions, Azure DevOps, Terraform (preferred) Distributed Architecture: Strong understanding of distributed systems, data/model versioning, and scalable deployment practices

Soft Skills:

Analytical mindset with strong technical rigor Excellent communication and collaboration skills Ability to work in agile, multicultural environments, taking ownership of projects Delivery-oriented with a focus on ownership and results