MLops Engineer

Duties & Responsibilities

• Provide timely service support for ML pipelines and workflows in production.
• Function as an MLops to support ML models in production.
• Enhance and optimize ML and AI modules and pipeline.
• Collaborate with other Business and Technology units to develop innovative solutions that meet

business needs with respect to functionality, performance, scalability, reliability.

Bachelors degree in computer science, Information Systems, Engineering, or a related field • Proficient in Python, Kubernetes. • Experience in MLops. • Monitor and support production environments to ensure optimal uptime and performance. • Diagnose, troubleshoot, and resolve application, infrastructure, and service issues in real-time. • Participate in on-call rotation to provide 24/7 production support coverage. • Collaborate with development, DevOps, and QA teams to identify root causes and implement long-term fixes. • Automate repetitive operational tasks through scripting and tooling. • Contribute to system reliability improvements, monitoring enhancements, and deployment processes. • Document incidents, resolutions, and best practices for continuous improvement. • Participate in release management, deployment validation, and rollback procedures. • Analyze production data and metrics to identify trends, potential risks, and optimization opportunities. • Ensure compliance with security and operational standards.

• Experience with orchestration tools (e.g., Databricks, ADF) for workflow management
• Demonstrated ability to lead and mentor teams while managing multiple priorities
• Strong communication and stakeholder management skills