Machine Learning Engineering - Intelligent Foundations and Experiences (IFX)
Tasks
- Automate tests and deployment for ML systems
- Build cloud based architectures for ML at scale
- Construct data pipelines for machine learning
- Design build and deliver machine learning models
- Develop and test model application code
- Ensure Responsible and Explainable AI practices
- Implement Continuous Integration and Continuous Deployment
- Manage code reduce vulnerabilities and support governance
- Monitor performance and availability of ML applications
- Retrain, maintain, and monitor models in production
- Select model data and features for training
- Train tune and validate machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agile | Apache Spark | Azure | Bias Variance | Cloud Computing | Cloud platform | Continuous Deployment | Continuous integration | Dask | Data Pipelines | Dimensionality Reduction | Distributed Computing | Explainable AI | Feature Selection | Google Cloud | Google Cloud Platform | Hyperparameter Tuning | Java | Machine Learning | Model Training | Model Validation | Monitoring | PyTorch | Python | Responsible AI | Scala | Scikit-learn | TensorFlow | Test automation
Education
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