Machine Learning Engineer

KEY RESPONSIBILITES AND SKILL SET

- Design and develop highly scalable, Real time systems using Hadoop ecosystem components(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

- Develop full stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks (e.g., Flask, React)

- learning models using Cloudera Machine Learning (CML).

• Perform performance tuning and optimization of data applications on Hadoop to ensure optimal resource utilization.

• Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit learn, XBoost), including model deployment.

- Design and develop highly scalable, Real time systems using Hadoop ecosystem components 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.

- Develop full stack applications and internal engineering tools using

Python, shell scripting, and modern web frameworks (e.g., Flask, React).

• Collaborate closely with data scientists to operationalize machine learning models using Cloudera Machine Learning (CML).

- Perform performance tuning and optimization of data applications on Hadoop to ensure optimal resource utilization.

KEY SKILLS

• Experience with Python, Java, Scala, or C++.
• ML Frameworks & Libraries - XGBoost, Scikit learn, Tensor Flow/keras, Hugging face (NLP/NLQ/Gen Al use cases)
• Full-Stack Development
• Performance Optimization
• Data Engineering & Ingestion Frameworks
• Collaboration with Data Science Teams