Senior MLOps Engineer, Buyer

Vinteden; Berlin; Vor Ort; EUR 90.000 - 140.000; Vollzeit

Zusammenfassung

Vinted is expanding its Buyer domain by hiring an MLOps Engineer to streamline ML model production, automated training, and robust deployment workflows. You will be the bridge to optimize our existing platforms (GCP/Vertex AI, Vespa, Triton) and raise the bar on production-ready ML systems.

You will work with a community of engineers, contribute to learning workshops, and help shape scalable MLOps practices across Europe.

Qualifikationen

• Experience deploying ML models in production with scalable pipelines.
• Strong knowledge of Kubernetes and containerized workflows.
• Experience with cloud ML platforms (GCP Vertex AI or SageMaker).
• Ability to design automated testing and quality gates for ML pipelines.

Aufgaben

• Productionise ML models with automated pipelines.
• Design and maintain continuous training workflows.
• Automate model serving and integration into Vespa/Triton.
• Build automated quality gates and governance for ML lifecycle.
• Collaborate with DS engineers and software teams.

Kenntnisse

GCP/Vertex AI

Kubernetes

Docker

ML deployment

Tools

ONNX

Jobbeschreibung

Brief info about Vinted

Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre‑loved clothing and lifestyle items, giving each piece a second life - or even a third.

The Vinted Group is made up of three business units that support this mission:

• Vinted Marketplace is Europe's leading platform for second‑hand fashion and a go‑to destination for all kinds of pre‑loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life.
• Vinted Go enhances the shipping experience with a vast network of over 500,000 pick‑up and drop‑off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high‑value pieces.
• Vinted Pay is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members.

Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people.

Information about the position

The Buyer domain's Data Science teams build and iterate on our most critical ML systems-like ranking, retrieval, and recommendations-that serve millions of users. As our ambition and the complexity of these models grow, we are scaling our MLOps capabilities to match:

We are hiring an MLOps Engineer to solve this. This is a high-impact "bridge" role, not to build new platforms, but to be the expert user of our existing platforms (GCP/Vertex AI, Vespa, Triton). Your mission is to take our Data Science team's work, rectify the current ad‑hoc solutions, and build the robust, automated, and high‑quality "path-to-production" our advanced models require.

Also by joining Vinted, you'll become part of an active community of engineers who are keen on sharing knowledge, organizing learning workshops and so much more!

In this position, you'll

• Productionise ML models: be responsible for migrating all existing model training code from experimental or proof‑of‑concept stages to robust and automated pipelines.
• Build continuous training (CT) pipelines: design, build, and maintain automated workflows for data preparation, model training, and batch scoring.
• Automate model serving & integration: package and deploy traditional ML models (e.g., in ONNX format) to our existing serving infrastructure, primarily Vespa and/or Triton.
• Close the deployment loop: automate model deployments where they are still manual. For example, building a GitHub Action that deploys a new model to Vespa, triggered by a webhook from a successful Vertex AI training pipeline.
• Build the missing quality gates: build the automated quality and evaluation gates that our pipelines lack today. This includes:
  • Establish and uphold ML Model Lifecycle Standards: Take ownership of and continuously improve the standards, quality, and governance of the complete ML model lifecycle.

About you

We are looking for an "ML-literate" Software Engineer, not a Data Scientist. You are a builder and an automator with a strong service mindset.

Must-have technical skills:

deep expertise in GCP/Vertex AI (or equivalents like SageMaker), Kubernetes, and Docker.

Automation expertise:

pro