Description

You will manage the operational lifecycle of machine learning models and the data pipelines that support them.

This role is hybrid.

Responsibilities

• Monitor AI system and data pipeline health, performance, and availability using established tools and dashboards.
• Detect, triage, and resolve incidents affecting AI systems and data infrastructure.
• Maintain and troubleshoot data pipelines to ensure reliable data flow for AI systems.
• Implement changes to production AI systems and pipelines using testing, validation, and rollback procedures.
• Automate routine operational tasks and workflows to enhance system reliability.

Required Skills

• Proven experience in MLOps, including deploying, monitoring, and maintaining ML models in production.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
• Proficiency with data processing frameworks including Spark and Kafka.
• Experience in troubleshooting and resolving complex AI system and data infrastructure issues.
• Knowledge of data quality management and its impact on AI performance.
• Experience with change management and implementing production updates with minimal disruption.
• Minimum of 3 years in IT operations, with at least 1 year focused on AI/ML systems and data pipeline support.
• Bachelor’s degree in Computer Science, Information Technology, or a related field.

Key Skills

Education

Bachelor’s degree in computer science, Information Technology