Machine Learning Engineer

Responsibilities

• Design and develop highly scalable, real‑time systems using Hadoop ecosystem components such as Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink, and NiFi.
• Build robust data ingestion and transformation frameworks using Java, Spark, Python, and shell scripting for ingesting multi‑model data (image, audio, video, unstructured documents) with both batch and real‑time processing.
• Develop full‑stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks (e.g., Flask, React).
• Perform performance tuning and optimization of data applications on Hadoop to ensure optimal resource utilization.
• Collaborate closely with data scientists to operationalize machine learning models using Cloudera Machine Learning (CML).
• Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit‑learn, XGBoost), including model deployment.