Senior MLOps Engineer

A company is looking for a Senior MLOps Engineer - Personalisation.

Key Responsibilities

Own and evolve the end-to-end ML lifecycle, including data ingestion, feature engineering, model training, and deployment

Design and manage automated CI / CD / CT pipelines for ML models, integrating with existing CI / CD patterns

Create and implement a robust observability framework for ML models in production, focusing on performance monitoring and operational health

Required Qualifications

7+ years of hands-on experience in an MLOps or DevOps role with a focus on machine learning systems

Proven experience building or evolving MLOps frameworks with quantifiable improvements

Expert-level knowledge of the GCP cloud stack, particularly Vertex AI

Deep expertise in managing observability stacks for real-time ML systems

Strong practical experience with Infrastructure as Code tools and CI / CD pipelines