ML Engineer
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Key skills for this role
About the Role
HCLTech is seeking an ML Engineer to design and deliver scalable real-time data and machine learning solutions using Hadoop ecosystem components. The role involves building data ingestion frameworks, operationalizing ML models, and developing full-stack applications.
Key Skills for This Role
Responsibilities
- Design and develop highly scalable real time systems using Hadoop ecosystem components
- Build robust data ingestion and transformation frameworks using Java, Spark, Python, and shell scripting
- Develop full stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks
- Collaborate with data scientists to operationalize machine learning models using Cloudera Machine Learning
- Perform performance tuning and optimization of data applications on Hadoop
Requirements
- Experience with Python, Java, Scala, or C++
- Experience with ML platforms such as CML, Spark MLlib, and Python ML libraries
- Experience designing scalable real time systems using Hadoop ecosystem components
- Experience building data ingestion and transformation frameworks
- Full stack development experience with Python and modern web frameworks
Full Job Posting
Job Objectives
- Design and deliver scalable real time data and machine learning solutions by building robust ingestion and transformation frameworks across Hadoop ecosystems.
- Enable end to end ML model operationalization and performance optimization, while supporting multi modal data processing and development of engineering tools and applications.
Key Responsibilities
- 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.
Skillset
- Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit learn, XGBoost), 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, TensorFlow/Keras, Hugging Face (NLP/NLU/Gen AI use cases)
- Full Stack Development
- Performance Optimization
- Data Engineering & Ingestion Frameworks
- Collaboration with Data Science Teams
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