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1 день назад

Senior Backend Software Developer (ML Platform)

Формат работы
remote/hybrid/onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR

Senior Backend Software Developer (ML Platform) (Python/AWS): Build backend services and tooling that turn machine learning experimentation into production-ready confidence with an accent on cloud-native infrastructure, MLOps platform capabilities, and reliable CI/CD-driven model deployment. Focus on integrating ML tooling (SageMaker Studio, MLflow), enabling reproducible experimentation, and partnering with ML engineers to remove workflow friction.

Company

Quebec-based company building AI-powered search and recommendations.

What you will do

  • Design, build, and evolve backend services and tooling across the machine learning development lifecycle.
  • Develop cloud-native infrastructure and automation using Python, AWS, Terraform, and CI/CD practices.
  • Partner with machine learning engineers and data scientists to understand workflows and deliver improvements.
  • Integrate and maintain ML tooling such as SageMaker Studio and MLflow while improving developer experience.
  • Make product-minded technical trade-offs to maximize value for internal users.
  • Provide technical leadership and drive continuous improvement within the engineering culture.

Requirements

  • Professional experience building backend applications in Python.
  • Strong experience building cloud-native solutions using Amazon Web Services (AWS).
  • Experience building or maintaining machine learning platforms, MLOps tooling, or infrastructure supporting ML workflows.
  • Strong understanding of infrastructure as code with Terraform and modern CI/CD practices.
  • Ability to work autonomously and communicate effectively with technical stakeholders.

Nice to have

  • Experience integrating or supporting SageMaker Studio or similar ML tooling.
  • Familiarity with Java or experience in polyglot engineering environments.
  • Background as a machine learning engineer or data scientist with interest in developer tooling.

Culture & Benefits

  • Work modes include in-person, hybrid, and remote; remote work may require travel for in-person team-building events.
  • Hybrid pillar days: offices gather two times a week to strengthen in-person collaboration.
  • Collaborative engineering culture with knowledge sharing and continuous learning.
  • Benefits support comfortable work from home.

Hiring process

  • Submit an application; hiring may use technology to help review candidates.
  • HR contacts candidates after application review.

Location: Montreal, Province of Quebec, Canada

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