About the role

  • MLOps Engineer responsible for industrializing and automating Machine Learning models in cloud environments. Join Expleo to enhance digital transformation in various sectors.

Responsibilities

  • Industrialization & Deployment of ML
  • Put ML models developed in Databricks into production
  • Build and maintain automated training, validation, and deployment pipelines
  • Containerize models and ML services when necessary (Docker + Azure Kubernetes Service)
  • Automation & CI/CD
  • Develop CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI)
  • Ensure reproducibility of ML environments
  • Monitoring & Observability
  • Implement model monitoring (data drift, concept drift, logs, metrics)
  • Ensure operational maintenance of deployed models
  • Instrument MLflow for experiment tracking
  • Infrastructure management
  • Administer and optimize Databricks usage (clusters, jobs, Delta Lake)
  • Work with Azure services: implement Infrastructure-as-Code using Terraform or Bicep
  • Define MLOps best practices (model tests, data tests, monitoring, automation)
  • Participate in data and model governance (catalogs, versioning, documentation)

Requirements

  • Degree in Computer Science or Data Science
  • 10 years' experience in MLOps, ML Engineering, or Data Engineering
  • Strong proficiency with Databricks (notebooks, MLflow, Delta Lake, clusters, jobs)
  • Strong proficiency with Microsoft Azure (data platform and compute)
  • Solid experience with Python and dependency resolution
  • Good knowledge of ML frameworks: scikit-learn, PyTorch, TensorFlow
  • Good knowledge of distributed architectures and big data processing (Spark)
  • Docker, Kubernetes (AKS), monitoring (Prometheus/Grafana or Azure Monitor)
  • CI/CD (GitHub Actions, Azure DevOps, GitLab CI)
  • Terraform, Bicep, or equivalent IaC tools
  • Fluent in French

Benefits

  • Technical and human support for each project
  • Strong ongoing career follow-up
  • Training programs to develop professional skills
  • Participation in dedicated special events
  • Integration into a dynamic team

Job title

MLOps Engineer

Job type

Experience level

SeniorLead

Salary

Not specified

Degree requirement

Postgraduate Degree

Location requirements

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