We are seeking a Senior Data Engineer with MLOps experience to build and operate scalable data platforms that support machine learning, AI, and LLM use cases. This role focuses on enabling end-to-end ML pipelines, from data ingestion and feature engineering to model deployment and monitoring.

Key Responsibilities

• Design and optimize large-scale data pipelines using Hadoop, Spark, and PySpark
• Build batch and real-time data processing workflows for AI/ML workloads
• Implement MLOps pipelines for model training, deployment, and monitoring
• Develop scalable feature engineering pipelines using Python
• Collaborate with ML engineers and data scientists to productionize AI/ML and LLM solutions
• Support cloud-based AI platforms on AWS / Azure / GCP

Requirements

• Strong experience in Hadoop, Apache Spark / PySpark
• Proficiency in Python; Scala is an advantage
• Hands-on experience with MLOps tools (Airflow, MLflow, Kubeflow, SageMaker, Azure ML)
• Knowledge of machine learning workflows and AI systems
• Experience with Docker, Kubernetes, and cloud platforms

Nice to Have

• Exposure to LLMs, NLP, or advanced AI use cases
• Experience with streaming tools (Kafka, NiFi)
• Consulting or enterprise project experience