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6 дней назад

Platform Engineer (AI)

200 000 - 400 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
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
Platform Engineer (AI): Building infrastructure and services for an AI interpretability platform, including shared APIs, experiment orchestration, data pipelines, and production systems with an accent on reliability, reproducibility, and compute-intensive model workflows. Focus on designing distributed platform capabilities, supporting training and inference workloads, and improving observability, performance, and failure recovery.

Location: San Francisco, CA; in person 5 days a week at the San Francisco HQ, with one company-wide remote week per month.

Salary: $200,000–$400,000 USD per year, plus equity and benefits.

Company

hirify.global is an AI interpretability research lab and public benefit corporation building agents and infrastructure to understand, monitor, and align AI models.

What you will do

  • Build shared services and APIs for launching work, accessing data, and retrieving results.
  • Develop systems to schedule, track, and recover long-running experiments and model workloads.
  • Create pipelines and storage interfaces for datasets, model activations, checkpoints, and evaluation results.
  • Improve deployment, observability, performance, reliability, and failure recovery across platform services.
  • Improve developer tooling so researchers and engineers can develop, test, and ship capabilities efficiently.

Requirements

  • 2+ years of experience building and operating production software.
  • Strong backend or systems engineering fundamentals in areas such as distributed systems, data infrastructure, cloud infrastructure, or developer tooling.
  • Experience owning a service or infrastructure component through development, deployment, and ongoing operation.
  • Ability to debug failures and reason about performance, reliability, and maintainability across system boundaries.
  • Ability to translate evolving research and engineering needs into practical technical solutions.
  • Interest in understanding how AI models work and building systems that make this understanding useful.

Nice to have

  • Experience supporting ML training, inference, evaluation, or research workflows.
  • Experience with job orchestration, GPU workloads, or large-scale data processing and storage.
  • Experience building shared infrastructure or developer tools for engineering teams.
  • Startup or frontier lab experience.

Culture & Benefits

  • Mission-driven environment focused on making AI interpretability accessible.
  • High-ownership, fast-moving team culture with an emphasis on initiative and continuous improvement.
  • Market-competitive salary, equity, and competitive benefits.
  • One company-wide remote week per month.

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