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1 день назад

Senior Machine Learning Engineer (AI)

Формат работы
remote (только United_states)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US/Argentina/Mexico +2 еще
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Senior Machine Learning Engineer (AI): Building and deploying scalable machine learning models to automate industrial supply chain processes with an accent on end-to-end pipeline ownership, production model monitoring, and data scalability. Focus on designing high-impact ML solutions, mentoring team members, and refining ML infrastructure to drive efficiency in a high-growth environment.

Location: Remote-first, must be based in North or South America

Company

hirify.global is a profitable, remote-first startup transforming the $10T global industrial supply chain industry through AI-driven automation.

What you will do

  • Design, build, and maintain scalable machine learning models for logistics automation.
  • Manage projects end-to-end, from data exploration to production deployment and monitoring.
  • Collaborate with engineering teams to align ML features with customer business needs.
  • Provide technical leadership, code reviews, and mentorship within the ML team.
  • Evaluate and implement frameworks to enhance ML infrastructure and development workflows.

Requirements

  • Senior-level experience in building and deploying production-grade machine learning models.
  • Proven ability to design scalable data pipelines for large datasets.
  • Strong proficiency in Python and ML frameworks like PyTorch, TensorFlow, or scikit-learn.
  • Experience with data processing tools such as Pandas and Spark.
  • Must be based in North or South America.
  • Ability to work independently in a fast-paced, product-focused startup environment.

Nice to have

  • Experience in high-growth startups or small, agile teams.
  • Familiarity with MLOps practices and relevant tooling.

Culture & Benefits

  • Remote-first, flexible work environment.
  • Strong engineering culture prioritizing code quality and sustainable velocity.
  • Opportunity to impact global supply chains and reduce industrial waste.
  • Culture of ownership and collaboration with a diverse, high-performing team.
  • Strong product-market fit in a critical, large-scale industry.

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