MLOps Engineer: Productionize ML on GCP & Vespa

Vinted; Oslo fylke; Hybrid; NOK 925,000 - 1,261,000; Full time

Benefits offered by this job

Share options programme

25 days paid annual leave

Newest MacBook models

Employee Assistance Program (EAP)

Frequent team-building events

Home office budget €540 for workspace

Daily lunch allowance

Company bike leasing

Monthly flexible benefits budget

Work from Home allowance

Defined Contribution Pension plan

Personal shopping budget on Vinted

NS mobility card

Dog-friendly office

Job summary

Vinted is seeking an ML-literate Software Engineer to bridge Data Science and Infrastructure. You’ll own the productionisation of ML models, build continuous training pipelines, and automate model serving using Vespa or Triton.

The role emphasizes pragmatic, scalable automation and strong collaboration across teams. You’ll join a growing Data Science ecosystem within a hybrid work model and enjoy professional development benefits, a generous annual leave policy, and access to the latest hardware

Qualifications

• We are looking for an ML-literate Software Engineer, not a Data Scientist.
• Must-have: deep expertise in GCP/Vertex AI (or equivalents), Kubernetes, and Docker.
• Solid automation experience with CI/CD (GitHub Actions, Jenkins, etc.).
• Understanding ML workflows (training, evaluation, inference) to debug pipelines and build quality gates.

Responsibilities

• Productionise ML models: migrate training code to robust automated pipelines.
• Build continuous training (CT) pipelines for data prep, training, and batch scoring.
• Automate model serving and integration to Vespa or Triton.
• Close the deployment loop by automating deployments (e.g., GitHub Actions to Vespa).
• Build automated quality and evaluation gates for pipelines.
• Own ML model lifecycle standards and governance.

Skills

GCP/Vertex AI

Kubernetes

Docker

CI/CD pipelines

GitHub Actions

Jenkins

ML concepts

Tools

Vespa

NVIDIA Triton

ONNX

Job description

Vinted is seeking an ML-literate Software Engineer to bridge Data Science and Infrastructure. You’ll own the productionisation of ML models, build continuous training pipelines, and automate model serving using Vespa or Triton.

The role emphasizes pragmatic, scalable automation and strong collaboration across teams. You’ll join a growing Data Science ecosystem within a hybrid work model and enjoy professional development benefits, a generous annual leave policy, and access to the latest hardware