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6 дней назад

VP, AI Engineering

200 000 - 490 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
director
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
VP, AI Engineering (AI/ML infrastructure and MLOps): Leading AI engineering strategy, teams, and production ML platforms with an accent on model deployment, data pipelines, inference infrastructure, and governance. Focus on scaling engineering organizations, integrating AI into applications, and solving challenges in reliability, latency, compliance, and cross-functional delivery.

Location: United States · Remote

Salary: $200,000–$490,000 base salary annually based on the tracked US senior-level AI engineering market.

Company

hirify.global is a specialist executive search firm focused on leaders who help organizations navigate AI transformation.

What you will do

  • Own the technical strategy and roadmap for AI/ML engineering, translating business priorities into scalable product and platform capabilities.
  • Build and lead an AI engineering organization, including hiring, technical standards, and reliable production delivery.
  • Drive the architecture and implementation of ML platforms, data pipelines, and inference infrastructure.
  • Partner with product, research, and data science teams to integrate models into customer-facing and internal applications.
  • Establish MLOps, monitoring, and governance practices covering production performance and compliance.
  • Advise leadership on technical feasibility, resource trade-offs, capability gaps, third-party AI tools, and vendor relationships.

Requirements

  • 10+ years of software engineering experience, including at least 5 years building, shipping, and operating production machine learning systems.
  • Experience leading and scaling engineering teams of approximately 5–30+ engineers through rapid growth and technical change.
  • Hands-on expertise in ML infrastructure, model deployment, experiment tracking, or MLOps.
  • Ability to translate ambiguous AI/ML requirements into engineering roadmaps and measurable business outcomes.
  • Experience collaborating with data science, product, and business teams to align technical decisions with organizational goals.
  • Comfort working in a remote, distributed environment and building alignment asynchronously across geographies and functions.

Culture & Benefits

  • Remote work in a distributed environment.
  • Opportunity to be considered for future senior AI engineering opportunities through the candidate network.
  • Roles may span professional services, technology, financial services, and manufacturing organizations.

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