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1 день назад

Senior MLOps Engineer

Формат работы
remote (только Brazil)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Brazil
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 MLOps Engineer: Building, deploying, and optimizing scalable machine learning infrastructure with an accent on ML deployment pipelines, CI/CD best practices, and monitoring systems. Focus on automating workflows, integrating models into production environments, and optimizing cloud-based systems for reliability and scalability.

Location: 100% Remote (São Paulo, Brazil)

Company

Leading nearshore staff augmentation provider headquartered in New York with 600+ tech professionals based in Latin America, partnering with U.S. companies on digital transformation projects.

What you will do

  • Design and maintain robust ML deployment pipelines for seamless model delivery.
  • Automate model training, deployment, and monitoring workflows to boost efficiency.
  • Collaborate with Data Scientists and Engineering teams to integrate models into production.
  • Optimize cloud infrastructure for scalability and reliability of ML systems.
  • Implement CI/CD best practices tailored for machine learning lifecycles.
  • Monitor production systems and troubleshoot performance or governance issues.

Requirements

  • Extensive experience as MLOps Engineer or Machine Learning Engineer in production environments.
  • Advanced proficiency in Python.
  • Proven track record deploying, monitoring, and maintaining ML models at scale.
  • Hands-on experience with Docker and Kubernetes for containerization and orchestration.
  • Strong expertise in cloud platforms such as AWS, Azure, or GCP.
  • Deep understanding of model governance and end-to-end ML lifecycle.
  • Experience with CI/CD pipelines for machine learning workflows.

Nice to have

  • Proficiency with ML orchestration tools such as Kubeflow, Airflow, or MLFlow.
  • Experience with Infrastructure as Code (IaC) using Terraform.
  • Familiarity with monitoring and observability tools in distributed environments.
  • Experience with LLMOps or GenAI pipelines.
  • Background in enterprise-scale infrastructure or regulated environments.
  • Familiarity with managed platforms like Databricks, SageMaker, or Vertex AI.

Culture & Benefits

  • 100% remote work with freedom to choose your location, laptop and reliable internet required.
  • Highly competitive USD pay exceeding market offerings.
  • Paid time off to support well-being and recharge.
  • Autonomy in managing time, focus on results over hours.
  • Work on high-impact projects with top U.S. companies.
  • Culture emphasizing work-life balance, engagement activities, and multicultural teams across 25+ countries.

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