ML Engineer
- Proficiency in Apache Spark and Spark MLlib for machine learning tasks.
- Strong understanding of predictive modeling techniques (e.g., regression, classification, clustering).
- Experience with distributed systems like Hadoop for data storage and processing.
- Proficiency in Python, Scala, or Java for ML development.
- Familiarity with data preprocessing techniques and feature engineering.
- Knowledge of model evaluation metrics and techniques.
- Experience with deploying ML models in production environments.
- Understanding of distributed computing concepts and parallel processing.
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