Data Scientist / ML Platform Engineer
Tasks
- Apply explainability techniques and document results
- Build LLM capabilities RAG pipelines prompt evaluation
- Build model serving infrastructure
- Configure environments manage access and handle secrets
- Create feature pipelines and automation
- Deploy models and manage model governance
- Develop train evaluate ML models
- Handle PII and track lineage with Unity Catalog
- Ingest data and build ELT ETL pipelines
- Monitor model performance and detect drift
- Orchestrate data pipelines and manage metadata
- Set up automated alerting and incident escalation
- Track experiments and manage model lifecycle with MLflow
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | Bash | CI/CD | Conda | Databricks | Databricks Workflows | Delta Live Tables | Delta Live) | Docker | Drift Detection | Evidently | Feature Store | Git | GitHub | Hugging Face | Hugging Face Transformers | Kafka | LIME | Langchain | Llamaindex | MLflow | Machine Learning | Model Monitoring | Prompt engineering | PyTorch | Python | RAG | REST API | SHAP | SQL | Scikit-learn | Shell | Snowflake | Spark | Spark Structured Streaming | Structured Streaming | TensorFlow | Unity Catalog | XGBoost
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