Machine Learning / AI Engineer
Tasks
- Collaborate on AI feature design and activation
- Deploy production models
- Develop feature engineering pipelines
- Implement CI/CD and code review
- Integrate ML outputs into LLM layer
- Manage model registry and versioning
- Monitor model drift and health
- Operate production scoring service
- Own machine learning lifecycle for AI features
- Participate in agile planning
- Retrain models with quality gates
- Train and evaluate models
- Triage production scoring failures
Perks/Benefits
- Flexible working hours
- Free parking
- Medicover sport and health
- Modern equipment
- Modern office
- Paid sick leave
- Paid vacation
Skills/Tech-stack
ADLS Gen2 | API Key | API key authentication | Application Insights | Argo CD | Automated retraining | Azure Blob | Azure Blob Storage | Azure DevOps | Azure DevOps Pipelines | Azure Event | Azure Event Hubs | Azure Monitor | Azure SQL | Azure Stream | Azure Stream Analytics | Blob Storage | CI/CD | Cosmos DB | DevOps Pipelines | Docker | Drift monitoring | Elasticsearch | Event Hubs | FastAPI | Feature Engineering | Gradient boosting | Kubernetes | LightGBM | MLOps | Managed Identity | Model Registry | NumPy | Pandas | Polars | PyTorch | Python | REST APIs | Redis | SHAP | SQL | Scikit-learn | Stream Analytics | Terraform | VNet | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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