Senior Machine Learning Engineer
Tasks
- Automate MLOps deployment and monitoring
- Build end-to-end machine learning pipelines
- Design ML algorithms for forecasting and prediction
- Develop machine learning models to production
- Engineer features for production readiness
- Implement real time prediction systems
- Maintain model version control and performance tracking
- Process data for model development
- Test validate and deploy production models
- Tune features and optimize model performance
Perks/Benefits
Skills/Tech-stack
Amazon Web Services | Anomaly Detection | Apache Kafka | Apache Spark | Cloud platform | Deep learning | Docker | Feature Engineering | Google Cloud | Google Cloud Platform | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Microsoft Azure | Model Deployment | Model Tuning | Model Validation | Prompt engineering | Prompt versioning | Python | Real Time | Real-time Processing | Retrieval-Augmented Generation | SQL | Series forecasting | Time Series | Time Series Forecasting | Time processing | Web Services
Education
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