Distributed Cloud | AI/Machine Learning Engineer
Tasks
- Build end-to-end machine learning pipelines
- Collaborate on feature engineering
- Containerize and run reproducible ML environments
- Deploy models on cloud platforms
- Detect model drift and ensure reliability
- Develop machine learning code in Python
- Implement MLOps model versioning and lifecycle
- Implement model monitoring and alerting
- Train test deploy predictive models
- Translate prototypes into production grade code
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | Azure Machine Learning | Data Warehousing | Docker | Drift Detection | Feature Engineering | GCP | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Model Drift | Model Drift Detection | Monitoring | Object-Oriented | Object-oriented programming | PyTorch | Python | SQL | SageMaker | Scikit-learn | Spark | TensorFlow | Vertex AI
Education
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