Senior Machine Learning Engineer at Itaú, driving innovation with data and AI solutions. Collaborating across teams to implement robust machine learning architectures and ensure scalable deployments.
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
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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