Accelerator - Data & AI Engineering (Paris)
Tasks
- Apply infrastructure as code
- Automate data ingestion and monitoring
- Build machine learning workflows
- Collaborate with cross-functional teams
- Conduct code peer review and technical documentation
- Define interface contracts between data products and applications
- Deploy machine learning models in production
- Design end-to-end data pipelines
- Develop ETL processes
- Ensure data quality standardization governance
- Implement data platform components
- Implement observability and data governance
- Integrate CI CD and containerized deployments
- Maintain pipeline reliability and scalability
- Mentor team members
- Monitor model performance and reproducibility
- Optimize data models for query performance
Perks/Benefits
- Health insurance
- Hybrid work
- Internal mobility opportunities
- Paid leave
- Professional development
- Public transport coverage
Skills/Tech-stack
AIOps | AWS | Airflow | CI/CD | DBT | Data Modeling | Data Warehousing | Datadog | Docker | ELT | ETL | Git | GitHub Actions | Grafana | Infrastructure as Code | Kubernetes | Logging | MLOps | Machine Learning | Observability | Python | SQL | Snowflake | Terraform | “as-code”
Education
Roles
AI | AI Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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