Senior ML Engineer
Tasks
- Architect ML pipelines and infrastructure
- Collaborate with data scientists
- Deliver technical findings in Agile teams
- Drive MLOps for automated deployment
- Implement ETL pipelines
- Improve system performance and scalability
- Maintain production ML systems
- Monitor model drift and retrain models
- Perform exploratory data analysis
- Preprocess and manage large scale datasets
- Version and monitor ML models
- Visualize statistical relationships
Perks/Benefits
Skills/Tech-stack
Data Analysis | Data labeling | Databricks | ETL | Entity Extraction | Exploratory Data Analysis | Git | Jupyter | Keyword extraction | Language Processing | MLOps | Machine Learning | Model Monitoring | Model retraining | Monte Carlo | Monte Carlo Simulation | Natural Language | Natural Language Processing | Predictive Maintenance | PySpark | SQL | Statistical Visualization | Time Series
Education
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