Назад
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7 часов назад

AI Operations Engineer

150 000 - 165 000$
Формат работы
remote (только USA)
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

Текст:
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TL;DR
AI Operations Engineer (Python/Distributed Data Systems): Building and operating large-scale data systems for AI training and evaluation pipelines with an accent on data ingestion, transformation, quality assurance, lineage, and high-throughput delivery. Focus on operating petabyte-scale storage and pipeline systems, enabling reproducible ML workflows, and optimizing data loading for accelerator-based training.

Location: 100% remote within the United States

Salary: $150,000–$165,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

  • Build and operate large-scale data systems powering AI training and evaluation pipelines.
  • Develop ingestion and transformation workflows across diverse data modalities.
  • Ensure data quality, lineage, versioning, reproducibility, and reliable delivery to training jobs.
  • Operate petabyte-scale storage and pipeline systems for high-throughput accelerator-based training.
  • Apply testing, CI/CD, code review, and strong software engineering practices.
  • Collaborate cross-functionally and communicate technical decisions clearly.

Requirements

  • 6+ years of data engineering experience, including significant work supporting ML or AI workloads.
  • Strong proficiency in Python and at least one JVM or systems language.
  • Deep experience with Spark, Ray, or Beam.
  • Hands-on experience operating petabyte-scale storage and pipeline systems.
  • Strong understanding of distributed systems, data modeling, and storage formats.
  • U.S. work authorization is required; new H-1B visa petitions cannot be sponsored.

Nice to have

  • Experience with large-scale multimodal datasets.
  • Familiarity with data quality tooling and dataset evaluation methodology.
  • Exposure to privacy-preserving data systems and regulated data handling.
  • Open-source contributions to data infrastructure projects.
  • Experience supporting frontier model training pipelines.

Culture & Benefits

  • Full-time direct W-2 employment.
  • Career growth opportunities within an established organization.
  • Remote work arrangement within the United States.

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