Description

You will design and implement scalable cloud architectures and data pipelines to support machine learning lifecycles.

Responsibilities

• Design AWS cloud architectures ensuring scalability and efficient resource utilization for MLOps.
• Develop data taxonomy and pipeline designs for ingesting, transforming, and serving data to ML models.
• Implement CI/CD pipelines for model training, deployment, and monitoring in collaboration with data science and DevOps teams.
• Provision infrastructure using code to ensure consistency and reproducibility across environments.
• Manage security and compliance by implementing access controls and encryption for sensitive data and models.

Required Skills

• 5+ years of experience in technical roles.
• Extensive experience with AWS cloud computing platforms.
• Strong proficiency in Python.
• Experience with AI workflow management tools such as Airflow, Kedro, or Luigi.
• Hands-on experience with MLOps, CI/CD, and the AI development lifecycle.
• Proven track record of delivering data products under strict security and model governance standards.
• Experience with data product development and analytical models.
• Knowledge of statistical modeling, machine learning algorithms, and predictive analytics.
• Familiarity with Agile practices and structured work planning.

Preferred Skills

• Proficiency in big data technologies like Hadoop or Spark.
• Experience with graph databases.

Key Skills

Education

Any Gradute