Senior Machine Learning Engineer

il y a 4 jours

Rabat, Rabat-Salé-Kénitra, Maroc AXA Global Business Services (AXA GBS) Temps plein

Overview:

As an experienced Machine Learning Engineer, you will be responsible for designing, developing, deploying, and optimizing large-scale AI models to meet business needs. You will play a key role in establishing a robust, scalable MLOps architecture, ensuring high performance, reliability, and maintainability of production solutions on Azure cloud.

Key Responsibilities:

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.

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

Experience:

  • 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

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

This role offers a unique opportunity to work on innovative projects within a dynamic environment, emphasizing operational excellence and digital transformation.

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