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4 дня назад

Director, Machine Learning

240 000 - 400 000$
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
Director, Machine Learning (AI/ML): Owns ML engineering strategy, team leadership, architecture, deployment pipelines, and monitoring systems for production machine learning initiatives with an accent on scalable systems, business impact, and responsible AI. Focus on building high-performing engineering teams, integrating ML into reliable production systems, and establishing governance and evaluation standards.

Location: United States, remote

Salary: $240,000–$400,000 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 ML engineering roadmap and strategy, translating business objectives into technical priorities and timelines.
  • Build, mentor, and lead ML engineering teams, including hiring, capability development, performance management, and career growth.
  • Design and oversee ML architecture, model development, deployment pipelines, monitoring systems, and engineering best practices.
  • Partner with product, data, and infrastructure teams to integrate ML capabilities into reliable production systems at scale.
  • Improve ML engineering processes, tooling, and infrastructure to accelerate time-to-value and reduce technical debt.
  • Communicate ML capabilities, limitations, and outcomes to stakeholders and executive leadership while establishing responsible AI standards.

Requirements

  • 8+ years of professional experience in machine learning, data science, or AI engineering.
  • At least 3 years in a leadership or staff/principal engineer role.
  • Experience building and shipping production ML systems with measurable business impact.
  • Experience leading and growing engineering teams, setting technical direction, and developing ML culture and capabilities.
  • Strong knowledge of model training, evaluation, feature engineering, deployment, and production monitoring.
  • Familiarity with MLOps pipelines, containerization, cloud platforms, and DevOps practices.

Culture & Benefits

  • Permanent remote work from the United States.
  • Opportunity to lead ML transformation initiatives across organizations.

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