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5 дней назад

Senior Technical Product Manager (Serverless AI)

Формат работы
remote (только Europe/United_states)/hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US/Netherlands
Вакансия из списка Hirify.GlobalВакансия из Hirify RU Global, списка компаний с восточно-европейскими корнями
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Описание вакансии

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TL;DR

Senior Technical Product Manager (Serverless AI): Building a consumption-based compute platform for running AI workloads with an accent on GPU scheduling, container runtimes, and cold start optimization. Focus on scaling the platform to 1,000+ users and designing high-performance, developer-first tooling including CLIs and APIs.

Location: Must be based in the Netherlands, Europe, or the United States

Company

hirify.global is an AI cloud platform providing high-end, training-optimized GPU infrastructure for AI practitioners.

What you will do

  • Co-own the Serverless AI product roadmap, focusing on Jobs, Endpoints, and DevPods.
  • Write technically precise PRDs specifying CLI syntax, API contracts, state machines, and billing models.
  • Manage technical trade-offs regarding GPU bin-packing, container cold starts, and storage mount performance.
  • Conduct technical customer discovery with ML engineers to translate qualitative insights into product actions.
  • Define and iterate on pricing, packaging, and tier strategies for the Serverless AI platform.
  • Own the technical content strategy, creating quickstart guides, tutorials, and reference architectures.

Requirements

  • 3+ years of product management experience in cloud infrastructure, AI/ML platforms, or developer tools.
  • Hands-on experience building and shipping infrastructure or platform products for developers or ML engineers.
  • Practical knowledge of containers (Docker, image registries, runtimes) and GPU computing for AI/ML (vLLM, TensorRT-LLM).
  • Proven experience shaping developer-facing APIs, CLIs, or SDKs.
  • Experience conducting technical customer discovery sessions with engineers.
  • Must be based in Amsterdam (Netherlands), Europe, or the United States.

Nice to have

  • Hands-on ML engineering background (training models, deploying endpoints).
  • Experience with Kubernetes for ML workloads (Kubeflow, KServe, Ray Serve).
  • Prior experience at a serverless or GPU cloud company.
  • Background in systems engineering, distributed systems, or SRE.

Culture & Benefits

  • Competitive salary and comprehensive benefits package.
  • Flexible working arrangements.
  • Dynamic and collaborative environment that values technical initiative and innovation.
  • Opportunities for professional growth within a high-impact, lean team.

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