Senior MLOps Engineer, Buyer
Vinteden · Amsterdam
Job description
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!
Read the full description (43 more sections)Show less
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: proven experience building robust CI/CD and automation pipelines (e.g., GitHub Actions, Jenkins, etc.).
ML-Literate: you understand ML workflows and concepts (training, evaluation, inference) well enough to debug pipelines and build meaningful quality gates.
Soft skills: a strong "service mindset," excellent communication, and the ability to act as a bridge between the highly technical worlds of Data Science and Infrastructure. You are pragmatic and driven to get high-quality work into production.
Bonus Points: familiarity with ML serving platforms like Vespa search engine or NVIDIA Triton and model formats like ONNX.
Willingness to learn and master new technologies and concepts.
We value pragmatism, big-picture thinking, curiosity, and problem-solving skills.
Work perks
The opportunity to benefit from our share options programme
25 days of paid annual leave
Newest MacBook models
Confidential Employee Assistance Program (EAP) for you and your family
Frequent team-building events
Home office support: we provide IT workstation equipment and a personal budget of up to €540 for home workplace furniture
A daily lunch allowance
Company bike leasing scheme
Monthly budget for a flexible benefits platform
Work from Home allowance
Collective Defined Contribution Pension plan
A personal monthly budget for shopping on Vinted
An NS mobility card
A dog-friendly office
Working at Vinted
Workation policy
Better balance holidays with workdays by working remotely! Up to 90 days per year in the EU, of these, 21 days can be spent globally. For non-EU citizens, it's 21 days worldwide. This can be combined with time off for vacation or personal time.
Individual learning budget
Each year, you’ll be given a learning budget (starting at €3,000), and a total of up to 10 working days over a 2-year period to support your personal and professional development.
Hybrid work
Our hybrid model, with 2 recommended office days a week, gives you and your team the flexibility to decide if and when you want to work from home, and when to catch up in person.
Equal opportunity
We welcome applications from everybody, regardless of your background, identity, or life experiences. Job openings come with guides, not checklists. If you’re excited about a role, but don’t identify with every point in the ‘About you’ section, apply anyway – you might still be the perfect match!
The annual gross salary range for this position is:
€89.000 — €121.400 EUR
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