Senior MLOps Engineer - Scale Production ML on Azure

SAS - Scandinavian Airlines; Solna kommun; On-site; SEK 900,000 - 1,300,000; Full time

Benefits offered by this job

Travel Perks

Health & Wellness

Discounts

Office near Frösundavik

Job summary

SAS - Scandinavian Airlines is seeking a Lead MLOps Engineer to own the end-to-end ML lifecycle and raise production readiness across the Azure-based platform. You will work with data scientists and offshore teams to ensure scalable, reliable ML deployments.

Based at SAS headquarters in Frösundavik, Solna, Stockholm, you will lead the standardization of MLOps practices, influence architectural choices, and mentor engineers while delivering value through AI-enabled solutions.

Qualifications

• Master's degree in computer science, engineering, ML, mathematics or related field.
• At least 5 years of hands-on ML engineering or MLOps, with production experience.
• Deep expertise across the ML lifecycle: tracking, packaging, CI/CD, deployment, monitoring and retraining.
• Experience operating ML in production on Azure cloud platforms.

Responsibilities

• Define and own the MLOps vision and standards for the AI & Automation team, covering the full lifecycle from experiment to production to retraining.
• Establish what production-ready looks like for ML at SAS, including packaging, testing, documentation, monitoring, and rollback.
• Work with data scientists to ensure operability in model development and handover to offshore operations.
• Build and mature the MLOps platform on Azure: model registry, CI/CD pipelines, automated retraining, feature management, deployment infra.
• Collaborate with Data Engineering and IT on infra, security, and cost-efficient operation of the ML platform.

Skills

ML engineering

Python

Azure

Docker

Kubernetes

CI/CD for ML

Leadership

Offshore collaboration

Education

Master's Degree in CS/Engineering/ML

Tools

Azure ML

Terraform

Job description

SAS - Scandinavian Airlines is seeking a Lead MLOps Engineer to own the end-to-end ML lifecycle and raise production readiness across the Azure-based platform. You will work with data scientists and offshore teams to ensure scalable, reliable ML deployments.

Based at SAS headquarters in Frösundavik, Solna, Stockholm, you will lead the standardization of MLOps practices, influence architectural choices, and mentor engineers while delivering value through AI-enabled solutions.