Junior Data Engineering Expert

2 weeks ago

Bhavnagar, Gujarat, India beBeeData Full time ₹ 15,00,000 - ₹ 25,00,000

Role Overview

At our organization, we are looking for a highly skilled and self-driven Junior Data Scientist to join our team.

The ideal candidate will have 3-4 years of experience in designing, implementing, and maintaining robust data science workflows that enable scalable, repeatable, and automated model training and deployment.

The successful candidate will independently architect, build, deploy, and maintain the entire ML infrastructure, focusing on pipeline-centric workflows.

  • Independently own and manage the full ML system lifecycle: from feature engineering and model development to production deployment and maintenance
  • Design and build scalable, automated pipelines for data ingestion and processing, model training at scale, evaluation and monitoring, retraining workflows
  • Build and maintain a platform-oriented architecture enabling multiple ML workflows with extensibility and reuse in mind
  • Deploy and operate ML workloads on cloud infrastructure using containerized environments
  • Implement robust CI/CD pipelines for automated testing, deployment, and rollback of ML services
  • Write clean, production-grade, well-tested Python code supporting these workflows
  • Maintain operational excellence for deployed pipelines: monitor performance, diagnose issues, and drive continuous improvement

Required Skills

  • Strong hands-on experience in Python, with proficiency in ML libraries such as scikit-learn, pandas, NumPy, PyTorch, tensorflow
  • Experience in building end-to-end ML pipelines as engineered software systems (not notebooks or isolated scripts)
  • Practical experience with ML workflow orchestration tools (e.g., Airflow, Kubeflow Pipelines, SageMaker Pipelines preferred but not mandatory)
  • Deep understanding of pipeline design patterns and best practices for production environments
  • Experience in building ML Pipelines for Computer Vision and NLP tasks

Good to Have Skills

  • Hands-on experience with cloud services for data science workloads
  • Understanding and experience with Kubernetes and Docker
  • Experience setting up and maintaining CI/CD pipelines for ML deployments
  • Ability to write and maintain unit tests, integration tests, and validation tests for ML pipelines and APIs
  • Prior work on platform architecture for multi-tenant ML workflows

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