MLOps Engineer
Expleo Group
full-time
Posted on:
Location Type: Hybrid
Location: Lausanne • 🇨🇭 Switzerland
Visit company websiteJob Level
SeniorLead
Tech Stack
AzureCloudDockerGrafanaKubernetesPrometheusPythonPyTorchScikit-LearnSparkTensorflowTerraform
About the role
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
MLOpsML EngineeringData EngineeringPythonscikit-learnPyTorchTensorFlowDockerKubernetesTerraform
Soft skills
communicationcollaborationproblem-solvingleadership
Certifications
Degree in Computer ScienceDegree in Data Science