Description

You will transform AI prototypes into production-grade pipelines and manage the full lifecycle of live models.

Responsibilities

• Transform prototypes into production-grade models by developing requirements with data scientists and AI strategists.
• Manage the full CI/CD cycle for live models, including testing, deployment, and retraining processes.
• Develop logging, alerting, and mitigation strategies to handle model errors and drift detection.
• Collaborate with technical teams to ensure compliance with AI and engineering standards.
• Contribute to AI infrastructure strategy and help establish coding standards across the team.

Required Skills

• 3+ years of industry experience in ML engineering.
• Strong proficiency in Python.
• Experience with AI workflow management tools such as Airflow, Kedro, or Luigi.
• Proficiency in big data technologies like Hadoop or Spark.
• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud.
• Deep understanding of the AI development lifecycle and Agile practices.
• Experience in data product development, analytical models, and model governance.
• Exposure to statistical modeling, machine learning algorithms, and predictive analytics.
• Bachelor's degree in Computer Science, Analytics, Mathematics, Statistics, Economics, Industrial Engineering, or Physical Sciences.

Preferred Skills

• Experience with graph databases.

Key Skills

Education

Bachelor's degree