Senior Machine Learning Operations Engineer

Role overview

Paramount is hiring a Senior Machine Learning Operations Engineer to own the operational layer for personalization and recommendation ML systems. The role focuses on ensuring trust in daily retraining and automated deployment pipelines, with fast detection and resolution when issues occur.

What you’ll do

• Own model traceability: ensure each production model has clear lineage (data, code, validation, and performance) and help evaluate tooling for versioning/metadata/model registry.
• Build end-to-end monitoring: monitor the full signal path including data arrival, feature distribution stability, model metrics, and serving latency vs. SLAs.
• Partner on data quality: work with Data Engineering to surface data quality issues, detect drift in upstream sources, and keep features fresh and reliable.
• Detect issues proactively: track drift over weeks, flag slow degradation early, and surface feature freshness problems before they cascade.
• Build diagnostic tooling: improve time-to-root-cause by ensuring proper logging/context (candidates, features, serving context) and creating dashboards.
• Own incident response for ML systems: maintain rollback/hotfix playbooks, define tradeoffs, implement automated gates blocking bad deployments, and run post-mortems.
• Coordinate post-deployment metrics: define and justify metrics to capture after deployments with ML engineers, data engineers, and stakeholders.

Basic qualifications

• 5+ years in ML engineering/applied ML/related ML roles with operational experience in monitoring, reliability, deployment, or incident response.
• Experience building or operating model registries, ML monitoring systems, or production ML pipelines.
• Strong understanding of ML systems end-to-end, including why feature staleness and distribution shift matter.
• Robust SQL skills for investigating data distributions, feature health, and model behavior.
• Ability to partner with DevOps/Platform teams to define infrastructure needs (without needing to own infra).

Nice to have

• Experience operating recommendation/personalization systems at scale (e.g., Paramount Streaming products).