The ideal candidate will be responsible for building and managing CI/CD pipelines for machine learning models using platforms such as Databricks and Azure ML. This role involves automating retraining, validation, and telemetry processes, collaborating with data modelers to ensure AI data pipeline readiness, and improving IT operations through automation. The AI Ops Engineer will also manage AI and infrastructure project timelines, risks, and coordination, act as a liaison between technical teams, business stakeholders, and data modelers, and track deliverables and KPIs to support agile execution. Gathering user feedback and requirements to guide feature development is also a key aspect of this role.

Key Responsibilities:

• Build and manage CI/CD pipelines for machine learning models using Databricks and Azure ML.
• Automate processes for retraining, validation, and telemetry of ML models.
• Collaborate with data modelers to ensure AI data pipeline readiness.
• Automate and improve IT operations, including incident detection, root cause analysis, event correlation, and predictive alerting.
• Manage project timelines, risks, and coordination for AI and infrastructure projects.
• Act as a liaison between technical teams, business stakeholders, and data modelers to ensure seamless communication and collaboration.
• Track deliverables, key performance indicators (KPIs), and support agile execution.
• Gather user feedback and requirements to guide the development of new features.

Qualifications:

• Proven experience in building and managing CI/CD pipelines for machine learning models.
• Strong knowledge of Databricks, Azure ML, and other relevant platforms.
• Experience in automating retraining, validation, and telemetry processes.
• Proficiency in collaborating with data modelers and ensuring AI data pipeline readiness.
• Expertise in automating IT operations, including incident detection, root cause analysis, event correlation, and predictive alerting.
• Excellent project management skills, with the ability to manage timelines, risks, and coordination.
• Strong communication skills to effectively liaise between technical teams, business stakeholders, and data modelers.
• Ability to track deliverables, KPIs, and support agile execution.
• Experience in gathering user feedback and requirements to guide feature development.
• Preferred Skills:
• Familiarity with additional AI and machine learning frameworks and tools.
• Knowledge of data engineering and data science best practices.
• Ability to stay updated with the latest advancements in AI and machine learning technologies.

Education:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

• Build and manage CI/CD pipelines for machine learning models using Databricks and Azure ML.
• Automate processes for retraining, validation, and telemetry of ML models.
• Collaborate with data modelers to ensure AI data pipeline readiness.
• Automate and improve IT operations, including incident detection, root cause analysis, event correlation, and predictive alerting.
• Manage project timelines, risks, and coordination for AI and infrastructure projects.
• Act as a liaison between technical teams, business stakeholders, and data modelers to ensure seamless communication and collaboration.
• Track deliverables, key performance indicators (KPIs), and support agile execution.
• Gather user feedback and requirements to guide the development of new features