Sr Machine Learning Engineer
Tasks
- Automate model retraining
- Build forecasting pipelines
- Design scalable machine learning systems
- Detect model drift
- Develop MLOps capabilities
- Develop data pipelines and feature engineering workflows
- Establish software engineering best practices
- Implement CI/CD for ML
- Implement batch and real time inference systems
- Implement rollback strategies
- Monitor model performance
- Operationalize forecasting simulation and scenario analysis
- Own end to end ML engineering lifecycle
- Productionize statistical Bayesian machine learning models
- Research emerging ML tools and methodologies
- Set up model versioning
Perks/Benefits
- N/A
Skills/Tech-stack
Automated retraining | Batch inference | Bayesian | CI/CD | Cloud Platforms | Containerization | Data Pipelines | Data Processing | Distributed data | Distributed data processing | Docker | Drift Detection | Feature Engineering | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Model Serving | Model versioning | Performance optimization | PyTorch | Python | Real Time | Real-time Inference | SQL | Scikit-learn | System design | TensorFlow | Testing
Education
N/A
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