MLOps Engineer

Role: MLOps Engineer Job Ref Id: JD-1283 Competence level: 5+ years Start date: 2026-12-01 End date: 2027-06-01 Extension option: Yes Scope: 100% Location: Stockholm Remote work: Remote Language: English Application deadline: 2026-11-01 Number of consultants: 1 Security clearance: No About the assignment We are looking for a MLOps contractor to own our ML platform infrastructure. You will sit in the Data Infrastructure team, which runs the GCP data and ML platform for the whole company. Vertical teams own their models and use-case logic; you own the platform they build on: training, serving, pipelines, and the tooling around them. This is one role covering company-wide ML infra, so you'll be the go-to person from day one. Responsibilities ML platform on GCP: Vertex AI, Kubeflow Pipelines and GKE-based training and serving infrastructure, kept reliable, secure and cost-efficient. Paved roads for ML teams: templates, CI/CD and self-serve tooling so data scientists ship models without filing tickets. Model lifecycle: registry, versioning, deployment, rollback, and monitoring for drift and serving health. Data integration: feature and training data flows across BigQuery, Airflow together with the data platform engineers. Infrastructure as code: everything managed through GitOps with Config Sync, with access following least privilege for PII and policy-tagged data. Cost and capacity: GPU/compute usage, quotas, and spend visibility per team. Requirements Mandatory 5+ years in MLOps