Professional
Telecommunications
In-House ML Deployment Framework Development
Software Developer
5 months
Developed and improved an internal Python framework used across departments to standardize the deployment and operation of business-critical machine learning applications.
Highlights
- Integrated automated monitoring capabilities with Databricks, removing manual configuration steps for internal teams.
- Refactored framework components to improve maintainability, readability, and overall developer experience.
- Translated requirements from developers, internal users, and stakeholders into framework capabilities that supported adoption across departments.
Technology Stack
Python
TensorFlow
Scikit-learn
Pandas
SQLAlchemy
CausalML
UV
pytest
SQL
PL/SQL
Spark SQL
SQLite
Databricks
Databricks Runtime
Unity Catalog
Databricks Clusters
SQL Warehouses
Asset Bundles
MLflow
CI/CD Pipelines
Azure DevOps
Azure
Azure Container Apps
Azure Container Registry
Azure Virtual Machine Scale Sets
Azure Key Vault
Azure Storage Accounts
Tags
#professional
#ml
#devops
#cloud
#internal-tooling