Description

You will lead the strategy and execution of AI data operations to support production machine learning environments.

This role is on-site.

Responsibilities

• Develop AI data operations strategies, quality standards, and automated validation workflows.
• Design and implement data quality monitoring systems, dashboards, and metric collection infrastructure.
• Oversee data labeling operations, vendor relationships, and dataset versioning processes.
• Lead architectural decisions for scalable data infrastructure and optimize pipeline efficiency.
• Manage cross-functional collaboration with ML engineers, data scientists, and DevOps teams.

Required Skills

• 7-10 years of experience managing AI/ML data pipelines in production environments.
• Expertise in large-scale data operations using Python and Azure.
• Hands-on experience designing automated data validation and labeling workflows.
• Proficiency in data management, dataset versioning, and SLA tracking.
• Proven experience in team management and leading cross-functional groups.
• Ability to manage vendor operations and drive cost optimization for data processes.
• Experience implementing data inventory tracking and quality assurance systems.
• Background in Machine Learning lifecycle practices.

Preferred Skills

• B.Tech, M.Tech (Dual), or MCA degree.

Key Skills

Education

Any Graduate