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