MLOps Support Engineer

About the role

The MLOps Support Engineer provides Tier 1 and Tier 2 operational support for AI/ML solutions, ensuring models and pipelines run reliably in production. This role focuses on stability, observability, and incident management rather than data science or feature development.

Key responsibilities

• Provide Tier 1/2 support, triage incidents, and coordinate escalations to Tier 3 engineering.
• Monitor pipeline health, model execution, and performance metrics; identify and resolve issues before they impact customers.
• Maintain runbooks, operational documentation, and support on‑call rotations.
• Work with engineering to improve supportability, observability, and reduce single points of failure.
• Build quarterly business reviews and evaluate champion/challenger models for promotion.

Required profile

• Early‑career professional with experience in operations, DevOps, SRE, or platform support.
• Strong troubleshooting skills in production environments and attention to model performance and bias.
• Collaborative mindset, eager to learn about complex predictive models and AI technologies.

Required skills

• SQL and scripting (Python, Bash) for automating ML workflows.
• Cloud platforms (AWS, GCP, Azure) and version control (Git).
• Monitoring tools (Grafana, PowerBI, New Relic) and MLOps tooling (MLflow, Databricks).
• Familiarity with containerization (Kubernetes) and LLM prompt engineering.