Description

Design and implement scalable cloud architectures and data pipelines to support machine learning lifecycles.

This role is on-site.

Responsibilities

• Design cloud architectures on AWS or multi-cloud environments to ensure scalability and efficient resource utilization for ML implementations.
• Develop data taxonomy and pipeline designs for ingesting, transforming, and serving data to machine learning models.
• Implement CI/CD pipelines for model training, deployment, and monitoring in collaboration with data science and DevOps teams.
• Provision infrastructure using tools like AWS CloudFormation or Terraform to ensure programmatic consistency and reproducibility.
• Optimize cloud resources for cost-effectiveness through auto-scaling, load balancing, and efficient compute usage.

Required Skills

• 5+ years of experience in technical roles with a focus on delivering data products.
• Extensive experience with AWS cloud computing platforms.
• Strong proficiency in Python.
• Experience with AI workflow management tools such as Airflow, Kedro, or Luigi.
• Proficiency in big data technologies like Hadoop, Spark, or similar frameworks.
• Experience with CI/CD and Agile practices.
• Knowledge of statistical modeling, machine learning algorithms, and predictive analytics.
• Experience with data product development, analytical models, and model governance.
• Proven track record of working within strict security and compliance standards.

Preferred Skills

• Experience with Azure or multi-cloud environments.
• Experience with graph databases.

Key Skills

Education

ANY GRADUATE