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3 дня назад

Senior Platform Engineer (AI/GPU)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
France/Romania/Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Senior Platform Engineer (AI/GPU): Building and operating a GCP-based GPU platform and self-service Kubernetes infrastructure for AI model training and serving with an accent on infrastructure-as-code, distributed systems, and platform reliability. Focus on designing GPU workloads, enabling data science teams through job scheduling and cost visibility, and establishing automated deployment paths for production AI services.

Location: Office-based in Paris, France; Montreal, Canada; or Bucharest, Romania

Company

hirify.global is a global video game company creating original gaming experiences across international studios.

What you will do

  • Design, build, and operate a GPU platform on GCP for AI workloads using infrastructure-as-code.
  • Deliver self-service compute for data science teams, including Ray on Kubernetes, job submission, queuing, quotas, and cost visibility.
  • Establish golden paths that enable product teams to deploy services without repeating operational work.
  • Support the deployment, hosting, and production operation of machine learning models.
  • Control infrastructure costs and improve system performance, reliability, and efficiency.
  • Collaborate with data science teams from proof of concept through production deployment and automate internal workflows with AI-powered systems.

Requirements

  • Significant experience as a Platform, DevOps, or MLOps Engineer with strong software engineering fundamentals and distributed systems knowledge.
  • Hands-on experience with Kubernetes, Terraform, GitOps, CRDs and operators, scheduling, autoscaling, node pool design, state management, ArgoCD, and Helm.
  • Solid experience with GCP.
  • Ability to work autonomously with a platform-as-a-product mindset, document solutions, measure adoption, and support data scientists as platform users.
  • Fluent English, written and spoken, is required.

Nice to have

  • Experience running or optimizing GPU workloads for machine learning training or inference in production.
  • Experience with distributed job scheduling such as KubeRay, Slurm, or Kubeflow.
  • Experience with cross-cloud networking between AWS and GCP.
  • Familiarity with MLOps tools such as MLflow, Weights & Biases, and model registries.
  • Real-world AWS experience.

Culture & Benefits

  • Access to an internal e-learning platform from the first day.
  • Access to a game library with hirify.global titles, competitor games, consoles, and board games.
  • Works council discounts for entertainment, fitness, cultural activities, and other services.
  • Career and development planning with a manager after one year.
  • Clubs, gym classes, bikes, organized sports weekends, and recreational activities.

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