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2 дня назад

Platform Engineer AI Compute

167 600 - 251 500$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Platform Engineer AI Compute (Kubernetes/GPU): Building and operating a shared AI compute platform for GPU workloads across cloud, on-premises, and air-gapped environments with an accent on Kubernetes orchestration, resource scheduling, and platform reliability. Focus on diagnosing workload performance, automating infrastructure upgrades, benchmarking training workloads, and guiding GPU capacity expansion.

Location: Onsite in San Diego or San Mateo, California, United States

Salary: USD 167,600–251,500 per year, plus bonus, benefits, and equity for regular full-time employees.

Company

hirify.global is a venture-backed defense-tech company developing intelligent systems, including Hivemind autonomy software, autonomous aircraft, and simulation technologies.

What you will do

  • Build and maintain software and configuration for running GPU workloads on Kubernetes.
  • Design quotas, scheduling priorities, permissions, and isolation for predictable multi-team compute sharing.
  • Automate deployment and upgrades of GPU services, including Run:ai, using infrastructure as code, Terraform, and Helm.
  • Investigate and resolve scheduling, configuration, storage, networking, and workload performance problems.
  • Build diagnostics connecting queue times, GPU utilization, memory requirements, and training throughput to developer experience.
  • Benchmark workloads, recommend GPU capacity and hardware, and deliver repeatable installations across cloud, on-premises, and air-gapped environments.

Requirements

  • Experience building and supporting production Kubernetes platforms, including GPU or distributed computing workloads.
  • Strong software engineering skills in Python, Go, or a comparable language.
  • Experience automating infrastructure deployment, configuration, and upgrades.
  • Practical Linux, networking, and storage troubleshooting skills.
  • Experience with shared resource scheduling, access controls, or workload isolation.
  • Ability to work directly with machine-learning engineers, understand their workloads, and turn recurring problems into maintained platform capabilities.

Nice to have

  • Experience with Run:ai or comparable GPU scheduling and resource-management systems.
  • Familiarity with distributed training and tools such as Ray or PyTorch.
  • Experience delivering on-premises or air-gapped platforms, or contributing to open-source infrastructure.

Culture & Benefits

  • Work on the AI Factory reference architecture used by internal engineering teams and delivered to customers.
  • Focus on the intersection of AI, distributed systems, Kubernetes, and defense.
  • Regular full-time employees receive pay within the listed range, bonus, benefits, and equity.
  • Offers are contingent on a cleared background and possible reference check.
  • hirify.global is an equal opportunity and affirmative action employer; accommodations are available for disabilities or special needs.

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