Tech Mahindra represents the connected world, offering innovative and customer-centric information technology experiences, enabling Enterprises, Associates, and the Society to Rise. It has 150,000+ professionals working for 1000+ Global Customers (including Fortune 500 companies) in 90 Countries. We're part of the esteemed Mahindra group, headquartered in India. Under a new CEO, Tech Mahindra is committed to a transformative journey with Scale @ Speed as our guiding principle.
ML Enginee
rKey Skills:
- Experience with Python, Java, Scala, or C+
- +ML Frameworks & Libraries – XGBoost, Scikit learn, Tensor Flow/keras, Hugging face (NLP/NLQ/Gen AI use cases
- )Full-Stack Developmen
- tPerformance Optimizatio
- nData Engineering & Ingestion Framework
- sCollaboration with Data Science Team
s
Key Responsibilities & Skillse
- tDesign 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
- .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
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