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17 часов назад

Software Engineer (AI/ML Infrastructure)

135 200 - 202 800CAD
Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Software Engineer (AI/ML Infrastructure): Develop scalable, reliable, and secure services for ML infrastructure including notebooks, model training, experimentation, serving, and LLM applications. Focus on building next-generation ML Infra services to improve ML development velocity and MLOps maturity across the company.

Location: Toronto, Canada

Salary: CA$135,200 - CA$202,800 annually

Company

hirify.global is a financial infrastructure platform used globally by businesses to accept payments and grow revenue, with a mission to increase the GDP of the internet.

What you will do

  • Design and build scalable, reliable, and secure services for ML lifecycle including notebooks, training, experimentation, serving, and LLM applications across multiple regions.
  • Create services and libraries enabling ML engineers to transition from experimentation to production seamlessly.
  • Collaborate with product teams and ML engineers to improve productivity.
  • Own and solve technical and product challenges across diverse systems and technologies.

Requirements

  • Location: Must be based in Toronto, Canada or able to work onsite.
  • 2+ years professional software development experience with service oriented architecture and large-scale distributed systems.
  • Experience with production ML platforms, MLOps solutions, or building LLM applications.
  • Experience running operations for high availability, low latency systems.
  • Experience partnering with teams to drive business outcomes.
  • Strong pragmatism in balancing ideal solutions and practical adjustments.

Nice to have

  • Experience building and shipping production AI agents.
  • Familiarity with LLMs and LLM frameworks.
  • Experience training and shipping machine learning models to production for critical business problems.

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