Develops and scales AI and analytics products in partnership with data scientists and business teams. Builds data models, pipelines, cloud-based applications and machine learning solutions using Python, SQL, Azure and/or GCP, while supporting DevOps practices, infrastructure reliability and reusable engineering tools.
Responsibilities
- Evaluate models and technologies through proofs of concept and experiments.
- Develop tested, standards-compliant code and contribute to reusable libraries and open-source projects.
- Build data models, model features, data quality tests, and ETL/ELT pipelines.
- Design and deploy analytics and machine learning applications across cloud environments.
- Operate and troubleshoot AI infrastructure using cloud-native services and platform engineering practices.
- Promote Dev
- Ops best practices, improve architectures, and coach colleagues in AI engineering.
Required Skills
- Python
- SQLData modeling
- ETL/ELT pipeline development
- Machine learning model deployment
- Azure cloud infrastructure
- Databricks
- Git
- Hub Actions and CI/CDTerraform
- Logging and monitoring technologies