Description

You will focus on implementation and technical execution within a small ML Ops team.

Responsibilities

• Build and maintain ML infrastructure and data pipelines.
• Develop CI/CD workflows specifically for machine learning deployment.
• Implement model monitoring systems to ensure performance stability.
• Construct a new platform to support the forecasting data science team.
• Execute data engineering tasks to support model training and deployment.

Required Skills

• 10+ years of professional experience in machine learning and data engineering.
• Extensive experience with AWS, specifically AWS SageMaker.
• Proficiency with Apache Spark for data processing.
• Hands-on experience with Airflow for workflow orchestration.
• Proven track record in CI/CD for machine learning (MLOps).
• Experience building and deploying data pipelines.
• Direct experience with model monitoring.
• Ability to work in a heavy implementation-focused role.

Key Skills

Education

ANY GRADUATE