Role Overview :

We are seeking a skilled Data Engineer - AI/ML to build and manage scalable data infrastructure that powers advanced machine learning and artificial intelligence solutions. This role focuses on designing high-performance data pipelines, enabling ML workflows, and ensuring reliable, production-ready data systems.

The ideal candidate has strong experience in distributed data systems, cloud platforms, and ML data preparation, with the ability to collaborate closely with Data Scientists and ML Engineers.

Key Responsibilities :

1. Data Platform Development :

- Design and develop scalable data lake and data warehouse architectures

- Build and maintain robust ETL/ELT pipelines

- Implement batch and real-time data processing systems

- Develop distributed data processing jobs using Apache Spark

- Implement data orchestration workflows using Apache Airflow

- Build streaming data pipelines using Apache Kafka

2. AI/ML Data Enablement :

- Prepare and transform large-scale datasets for ML model training

- Build feature engineering pipelines and support feature store architecture

- Ensure data quality, validation, and governance for AI systems

- Optimize data pipelines for ML experimentation and production workflows

- Enable reproducible datasets and version-controlled ML data

3. Cloud & Infrastructure :

- Deploy and manage data infrastructure on cloud platforms such as

- Amazon Web Services,

- Microsoft Azure, or

- Google Cloud Platform

- Implement scalable storage solutions (S3, Blob Storage, BigQuery, etc.)

- Work with containerization tools like Docker

- Orchestrate services using Kubernetes

- Apply Infrastructure as Code (Terraform preferred)

4. MLOps & Production Support :

- Support ML lifecycle management using tools like MLflow or Kubeflow

- Build CI/CD pipelines for ML workflows

- Monitor data drift and data pipeline performance

- Implement logging, monitoring, and alerting mechanisms

- Ensure data compliance and security best practices

Required Qualifications :

- 4-6 years of hands-on experience in Data & AI/ML

- Strong experience with TensorFlow / PyTorch

- Solid understanding of statistics, model training & fine-tuning

- Experience with Spark, PySpark & scalable data pipelines

- AWS Certified - ML Specialty & Developer Associate preferred

- Strong communication skills & collaborative mindset

Preferred Qualifications :

- Experience working closely with Data Scientists and ML Engineers

- Knowledge of feature stores and model serving architectures

- Familiarity with ML libraries such as TensorFlow, PyTorch, or scikit-learn

- Experience with real-time analytics systems