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Vinted

C2C marketplace for pre-owned fashion.

Lead Site Reliability Engineer - ML Platform

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeKaunas, Kaunas City Municipality, Lithuania

About the Job

Requirements

  • Have a track record of leading technical problem-solving for complex, domain-level systems.
  • Have deep experience with Kubernetes, Linux internals, and high-scale networking.
  • Have working experience with programming or scripting; Go is a plus, and experience with other languages is also welcome.
  • Choose tools based on long-term impact rather than personal preference.
  • Have excellent written and spoken English and the ability to articulate technical risks to technical and non-technical stakeholders.
  • Be a coach and mentor who values enabling an entire team, rather than writing every line of code personally.

Responsibilities

  • Lead the technical roadmap for the ML Platform, ensuring training and inference infrastructure scales to meet ML/AI demands.
  • Architect high-performance inference solutions focused on low-latency delivery and efficient GPU utilization across clusters.
  • Define and drive reliability standards, including service-level objectives, error budgets, and observability for model-serving systems.
  • Mentor and grow senior engineers within the team, fostering technical excellence, pragmatism, and continuous learning.
  • Identify and solve systemic bottlenecks in the deployment lifecycle by writing requests for comments and collaborating on long-term architectural improvements.
  • Oversee integration of deployment workflows with automated experimentation patterns, such as A/B testing and shadow deployments.
  • Communicate architectural risks, planned changes, and strategic reliability trade-offs to stakeholders.
  • Partner with Data Scientists and Platform teams to bring machine-learning innovation into production.
  • Orchestrate a fleet of more than 200 high-performance GPUs for model training, production inference, and large language model serving.

Desired Qualifications

  • Experience with GPU workloads and inference frameworks such as KServe, vLLM, or NVIDIA Triton.

About the Company

Vinted

C2C marketplace for pre-owned fashion.

Vinted is an online marketplace where people buy and sell second-hand clothing and accessories. It operates as a consumer-to-consumer (C2C) platform that lets individuals list pre-owned items for sale and others purchase them. Revenue comes mainly from a Buyer Protection fee charged on each transaction, which covers customer support, shipping tracking, and refunds. The platform targets those interested in affordable, sustainable fashion and the circular economy, appealing to users who want to declutter, discover unique items, and shop more environmentally friendly. Vinted’s approach centers on peer-to-peer re-commerce, offering a simple way to trade clothing within a global community, with a focus on accessibility and sustainability rather than new-product manufacturing.

Company size
1,001-5,000
Company stage
Private
Total funding
$559.6M
Headquarters
Vilnius, Lithuania
Founded
2008

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