Machine Learning Operations Engineer, Booksy

• A track record of putting models into production alongside Data Scientists — classic ML, LLM/GenAI, or both
• Deep understanding of the ML lifecycle from prototype to production, including real-time serving, feature stores, autoscaling, and blue/green deployments
• Strong Python and SQL skills
• Hands-on GCP experience, especially Vertex AI, Kubeflow pipelines, and BigQuery — or strong fluency on an equivalent cloud with a clear ability to get to Vertex fast
• Solid CI/CD and production-monitoring experience, including model registries, versioning, drift detection, and automated retraining
• At a minimum we require conversational-level English language skills. English is our company language and is used for business-wide communication

Desirable

• As a Senior ML / MLOps Engineer, you'll be a foundational hire in our new Data Science & Applied AI function — working in close partnership with our Data Scientists to take intelligent systems from prototype to production, and keep them performing once they're live
• You'll own the productionisation of our machine learning work end to end: real-time serving against SLAs, a standardised CI/CD path to production, GenAI and RAG system deployment, and the monitoring infrastructure that catches drift and quality degradation before business KPIs move
• You'll work on a GCP-native stack — Vertex AI, BigQuery, dbt, Airflow, and Terraform — on problems that matter from day one, with the autonomy to shape how the function scales and who joins it next
• You'll collaborate closely with Data Scientists, Platform, and Engineering, acting as both a technical owner and an advocate for Data Science needs across the organisation

• Kindly submit your application and CV in English to ensure it is successfully reviewed