Lead Machine Learning Engineer
Tasks
- Apply responsible AI and explainable AI
- Automate testing for ML deployments
- Build cloud-based ML architectures
- Deploy ML models to production
- Design ML architectures
- Design ML models and components
- Develop and review ML application code
- Ensure availability and performance
- Monitor and maintain models in production
- Optimize data pipelines
- Reduce vulnerabilities through code governance
- Retrain models in production
- Train and tune machine learning models
- Validate ML models
Perks/Benefits
Skills/Tech-stack
AWS | Apache Spark | Azure | Bias Variance | Cloud platform | Continuous Deployment | Continuous integration | Dask | Data Pipelines | Data Validation | Dimensionality Reduction | Distributed Computing | Explainable AI | Feature Selection | Google Cloud | Google Cloud Platform | High Availability | Hyperparameter Tuning | Java | Machine Learning | Model Monitoring | Model Training | PyTorch | Python | Responsible AI | Scala | Scikit-learn | TensorFlow | Test automation
Education
Regions
Countries
States
Cities
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