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2 дня назад

VP, AI Engineering

220 000 - 410 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
c_level
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): Owns technical strategy, builds engineering teams, and ships production AI/ML systems end-to-end with an accent on scalable architectures, data pipelines, model quality, and production reliability. Focus on establishing MLOps and governance frameworks, making build-versus-buy decisions, and balancing technical robustness with business priorities.

Location: United States · Remote

Compensation: $220,000 median offers, with top-tier packages reaching $410,000 annually.

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 initiatives, aligning priorities with business outcomes and architecture constraints.
  • Build and lead a high-performing AI/ML engineering team through hiring, mentoring, and setting standards for engineering rigor.
  • Partner with product, data science, and platform teams to translate business requirements into scalable ML systems.
  • Ship production AI/ML systems end-to-end, from problem definition and data strategy through deployment, monitoring, and continuous improvement.
  • Establish engineering standards, MLOps practices, and governance frameworks for performant, auditable, and maintainable models.
  • Evaluate emerging ML tools, frameworks, and infrastructure while making build-versus-buy decisions and communicating trade-offs to stakeholders.

Requirements

  • 10+ years of software engineering experience, including at least 5 years building, shipping, or leading production AI/ML systems.
  • Experience managing and growing engineering teams of 3+ people, including hiring and developing engineers and leaders.
  • Strong understanding of ML workflows, including data pipelines, feature engineering, model training, evaluation, and deployment.
  • Hands-on experience writing model-training code and working with PyTorch, TensorFlow, and scikit-learn.
  • Experience setting technical strategy, making architectural trade-offs, and translating business needs into engineering roadmaps.
  • Ability to communicate technical possibilities, risks, and priorities to both technical and non-technical audiences.

Culture & Benefits

  • Permanent remote work based in the United States.
  • Opportunity to be considered for future AI transformation leadership roles through the candidate network.

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