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Senior Machine Learning Operations Engineer

3 semanas atrás

Brasil beBeeMLOps Tempo inteiro US$90.000 - US$120.000

We are looking for a skilled professional to design and implement innovative machine learning pipelines. As a Senior Machine Learning Operations Engineer, you will be responsible for managing cloud-based resources, automating model deployment, and optimizing AI/ML infrastructure to deliver scalable, precise, and high-performing machine learning solutions.

Responsibilities
  • Develop and implement efficient MLOps pipelines using container orchestration tools and infrastructure-as-code frameworks.
  • Collaborate with data scientists and engineers to develop tailored MLOps solutions and automate model deployment using scripts and tools.
  • Configure and manage cloud-based resources to support AI/ML workloads, ensuring consistency and scalability.
  • Monitor and optimize AI/ML infrastructure performance, identifying and resolving bottlenecks to improve overall system efficiency.
Requirements
  • Extensive experience deploying machine learning models to cloud environments and strong expertise in container orchestration tools.
  • Proficiency in infrastructure-as-code (IaC) frameworks for cloud resource management and hands-on experience with streaming data platforms.
  • Solid understanding of data cleaning, transformation, and ETL processes, as well as experience with CI/CD tools and pipelines.
What We Offer
  • 100% Remote Work: Enjoy the flexibility to work from anywhere and maintain a healthy work-life balance.
  • Competitive Compensation: Earn a highly competitive salary that reflects your skills and experience.
  • Paid Time Off: Take advantage of generous paid time off policies to recharge and focus on personal well-being.
  • Opportunities for Growth: Join a dynamic team and collaborate with seasoned professionals to develop new skills and advance your career.
About This Opportunity
  • This is a mid-senior level position requiring a strong background in machine learning operations and cloud computing.
  • The ideal candidate will have experience working with large datasets, implementing MLOps pipelines, and collaborating with cross-functional teams.