ML Ops Engineer Role Overview

We’re hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine‑learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: you’ll design and operate data pipelines that feed models, and you’ll build the tooling that trains, deploys, monitors, and retrains them. You’ll work closely with research engineers and product teams, taking models from experimentation to production‑grade systems with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands‑on engineering role focused on making ML systems work reliably at scale.

What You’ll Work On

• Productionizing models: packaging, deployment, versioning, and rollback
• Designing CI/CD pipelines for ML (training → validation → deployment)
• Implementing model monitoring (data drift, prediction drift, performanc...