Machine Learning Engineer

Key Responsibilities:

· Design and develop scalable data pipelines across Hadoop (Hive, Impala, Spark, Kafka, Iceberg) and Teradata environments.

· Build ingestion and transformation frameworks using Java, Spark, Python and shell scripts.

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

· Create APIs and microservices to expose data and ML models securely to downstream systems and user interfaces.

· Collaborate with data scientists to operationalize ML models using Cloudera Machine Learning (CML)

· Build and deploy GenAI/LLM-powered applications for intelligent data interaction, summarization, and automation.

· Implement enterprise-grade security controls including RBAC, LDAP, Kerberos, Apache Ranger, and row-level access.

· Tune and optimize data applications for performance across Hadoop and Teradata, ensuring efficient resource utilization.

· Support sandbox environments for prototyping, enabling users to build ML models, dashboards, and data pipelines.

Required Skills & Experience:

· Data Engineering: Strong experience with Hadoop ecosystem (Hive, Impala, Spark, Kafka, Iceberg, Ranger, Atlas), Teradata and data pipeline orchestration.

· Full Stack Development: Proficiency in Python, Shell scripting, REST APIs, and web frameworks (Flask, React, etc.).

· Machine Learning & AI: Hands-on experience with ML platforms (CML), Spark MLlib, Python ML libraries (scikit-learn, XGBoost), and model deployment.

· GenAI/LLM Applications: Familiarity with building applications using large language models (e.g., OpenAI, Hugging Face, LangChain) for enterprise use cases.

· Security & Governance: Experience with enterprise data security (LDAP, Kerberos, RBAC), data masking, and access control.

· Performance Tuning: Proven ability to optimize data applications and queries in large-scale environments (Hadoop, Teradata).

· Tools & Platforms: Cloudera Data Platform (CDP), Informatica, QlikSense, Apache Oozie, Git, CI/CD pipelines.

· Soft Skills: Strong analytical and problem-solving skills, excellent communication, and ability to work in cross-functional teams.