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6 дней назад

Principal Machine Learning Engineer (Ads Modeling)

197 400 - 256 600$
Формат работы
onsite
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

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TL;DR
Principal Machine Learning Engineer (Ads Modeling) (machine learning/deep learning): Advancing personalized ads recommendation algorithms using user behavior data and large-scale compute with an accent on foundational research, model validation, and metric design. Focus on designing the modeling roadmap, solving complex cross-team problems, and productionizing research with engineering and product teams.

Location: Mountain View, California, USA

Gross annual base salary: $197,400–$325,400 USD, depending on salary zone.

Company

hirify.global develops a leading game engine and 3D technology platform used across games, XR, web, automotive, manufacturing, and healthcare.

What you will do

  • Identify opportunities and design a modeling roadmap addressing customer needs.
  • Drive foundational research into new machine learning models and paradigms.
  • Use rich user data and large-scale compute to validate models rapidly.
  • Advance ads recommendation algorithms and personalized advertising experiences.
  • Collaborate with engineering and product teams to productionize research.

Requirements

  • Hands-on experience applying state-of-the-art machine learning and deep learning models to complex real-world problems.
  • Expertise in user behavior modeling.
  • Proficiency in Python, PyTorch, and deep learning frameworks.
  • Strong understanding of metric design, large-scale data analysis, and distributed computing frameworks.
  • Ability to drive projects end-to-end, solve critical cross-team problems, and deliver measurable business results.
  • Sufficient English proficiency for frequent professional verbal and written communication.

Culture & Benefits

  • Health, life, and disability insurance, with offerings varying by country and employment status.
  • Employee stock ownership and retirement or pension plans.
  • Vacation, personal days, parental leave, and family-care programs.
  • Mental health support, employee resource groups, and global employee assistance.
  • Training and development programs, volunteering, and donation matching.
  • Commute subsidy and office food snacks.

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