Accelerator - Data & AI Engineering (Paris)
Tasks
- Automate data ingestion and monitoring systems
- Build and maintain ETL processes and machine learning workflows
- Deploy models and monitor model performance
- Design and implement end-to-end data pipelines
- Develop and optimize data models
- Drive MLOps and AIOps practices
- Ensure data quality standardization observability governance
- Implement CI CD integrations and containerized deployments
- Maintain reproducibility of ML experiments
- Mentor team members and share knowledge
- Participate in peer review and technical documentation standards
- Translate business requirements into technical solutions
Perks/Benefits
- Employer-Matched Retirement Plan
- Extended parental leave
- Group savings plan
- Health insurance coverage
- Hybrid work arrangement
- Internal and international mobility opportunities
- Learning and development opportunities
- Paid time off
- Public transport coverage
- Remote work up to 2 days per week
- Second medical opinion covered
- Teleconsultation
- Wellness programs
Skills/Tech-stack
AIOps | AWS | Apache Airflow | CI/CD | Cybersecurity | DBT | Data Governance | Data Modeling | Data Pipelines | Data Privacy | Data Quality | Data Warehousing | Datadog | Docker | ELT | ETL | Git | GitHub Actions | Grafana | GxP | Infrastructure as Code | Kubernetes | Logging | MLOps | Machine Learning | Machine Learning Workflows | Model Deployment | Monitoring | OpenShift | Pipeline Orchestration | Python | SQL | Snowflake | Terraform | Version control | “as-code”
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