ML Engineer
HUF 7500K-9000K (estimate) Mid-level Full Time
Tasks
- Apply explainability methods
- Build and operate model training and deployment pipelines
- Collaborate in cross functional agile teams to deliver AI solutions
- Design build and operate generative AI and LLM applications
- Develop model lifecycle management and feature stores
- Implement LLMOps for prompt version management and evaluation
- Implement MLOps CI CD for models and reproducible deployments
- Implement monitoring and observability for models in production
- Implement responsible AI risk management and compliance
- Improve data quality frameworks and tools
- Maintain large scale AI data infrastructure
- Track data drift and model drift
- Validate and scale machine learning algorithms
Perks/Benefits
Skills/Tech-stack
AI Search | Azure AI | Azure AI Search | Azure Data | Azure Data Factory | C# | C++ | CI/CD | Data Factory | Databricks | Databricks AI | Databricks AI Search | Deep learning | Docker | Fine Tuning | Hugging Face | Infrastructure as Code | Java | Kubernetes | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | MLOps | MLflow | Machine Learning | NumPy | PGVector | Pandas | Prompt engineering | PyTorch | Python | Ray | Retrieval-Augmented Generation | SQL | Scala | Scikit-learn | Spark | TensorFlow | Vector Databases | “as-code”
Education
N/A
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