Analyst, ML Engineering
USD 139K-265K (estimate) Senior-level Full Time
Tasks
- Build ML data pipelines ingestion transformation validation
- Conduct ML experimentation feature engineering model selection performance evaluation
- Deploy and maintain ML models in cloud environments
- Develop train evaluate machine learning models
- Document ML components data preparation model configuration test results
- Execute testing for data pipeline models and integration
- Implement data quality checks anomaly detection dataset preparation
- Maintain model registries versioning change logs
- Monitor deployed models performance and flag anomalies
- Perform code reviews and technical walkthroughs
Perks/Benefits
- N/A
Skills/Tech-stack
Anomaly Detection | Azure DevOps | Azure Machine Learning | CI/CD | Data Ingestion | Data Privacy | Data Quality | Data Transformation | Data Validation | Docker | Experiment tracking | Feature Engineering | Git | GxP | Huggingface | Langchain | Language Processing | MLOps | MLflow | Machine Learning | Model versioning | Natural Language | Natural Language Processing | NumPy | Pandas | Prompt engineering | PyTorch | Python | RAG | Responsible AI | Scikit-learn | Semantic Kernel | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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