ML Engineer
HUF 7500K-9000K (estimate) Mid-level Full Time
Tasks
- Build and maintain AI data infrastructure
- Collaborate in agile cross-functional teams
- Deliver features on agreed backlog
- Design build and operate LLM applications
- Develop and maintain MLOps pipelines
- Implement LLMOps practices
- Implement monitoring and observability for models
- Improve data quality frameworks
- Manage model lifecycle
- Support responsible AI practices
- Validate and scale machine learning algorithms
Perks/Benefits
Skills/Tech-stack
AI Search | Azure AI | Azure AI Search | Azure Data | Azure Data Factory | CI/CD | Data Drift | Data Drift Detection | Data Factory | Data Quality | Data Quality Evaluation | Databricks | Docker | Drift Detection | Feature Stores | Guardrails | Hugging Face | Infrastructure as Code | Kubernetes | LLM APIs | LLM Evaluation | LLMOps | Langchain | Lifecycle Management | Llamaindex | MLOps | MLflow | Model Drift | Model Drift Detection | Model Lifecycle | Model Lifecycle Management | Model Registry | NumPy | Observability | PGVector | Pandas | Prompt management | PyTorch | Python | Quality evaluation | SQL | Scikit-learn | Spark | TensorFlow | Vector Databases | “as-code”
Education
N/A
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