Machine Learning Engineer (Banking, 1-year renewable contract)

Key Responsibilities

• Design and develop highly scalable real-time data processing systems using Hadoop ecosystem technologies such as Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink, and NiFi
• Build robust batch and real-time data ingestion and transformation frameworks using Java, Spark, Python, and shell scripting
• Develop solutions to process and manage multi-model data including images, audio, video, and unstructured documents
• Develop full-stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks such as Flask and React
• Collaborate closely with data scientists to operationalize and deploy machine learning models using Cloudera Machine Learning (CML)
• Perform performance tuning and optimization of Hadoop-based data applications to improve scalability and resource utilization
• Design and implement scalable enterprise data processing pipelines and frameworks
• Support deployment, troubleshooting, monitoring, and continuous improvement of big data and ML platforms
• Work closely with cross-functional teams to deliver scalable and high-performing data engineering solutions

Key Requirements

• Strong hands-on experience with Hadoop ecosystem technologies including Spark, Kafka, Hive, Flink, NiFi, Trino, Iceberg, Ranger, and Ozone
• Experience building scalable real-time and batch data processing applications
• Strong programming and scripting skills in Java, Python, and shell scripting
• Experience developing data ingestion and transformation frameworks for structured and unstructured data
• Hands-on experience with machine learning platforms such as Cloudera Machine Learning (CML), Spark MLlib, scikit-learn, and XGBoost
• Experience operationalizing and deploying machine learning models into production environments
• Experience developing full-stack applications and internal engineering tools using Flask, React, or similar frameworks
• Strong understanding of distributed computing, big data architectures, and data pipeline orchestration
• Experience with performance tuning and optimization of Hadoop or distributed data applications
• Strong analytical, troubleshooting, and problem-solving skills
• Experience within enterprise-scale data engineering or banking environments is preferred