Remote Principal Machine Learning Engineer - MLOps

Description:

• We are looking for a Principal Machine Learning Engineer focused on ML Ops and ML Platform development.
• This engineer will join a centralized Machine Learning Engineering team, supporting scalable AI systems across Digital and Retail use cases.
• The ideal candidates will bring hands-on expertise in MLOps, distributed Machine Learning platforms, and experience working in cloud-native environments, especially Azure.
• Candidates should have 8+ years of relevant experience in Machine Learning, Data Engineering, or MLOps roles.
• A proven track record of building, deploying, and maintaining ML systems in production environments is required.
• Proficiency with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn is necessary.
• Hands-on experience with MLflow, SageMaker, and Azure ML for model training, tracking, and deployment is essential.
• Candidates should be skilled in CI/CD pipelines for ML using GitHub Actions, Azure DevOps, and Terraform.
• Expertise in model observability, monitoring, and drift detection is required.
• Experience building and managing ML pipelines using Airflow, Azure Data Factory, and related tools is necessary.
• Cloud infrastructure expertise with Azure (primary) and AWS (secondary) is required.
• Containerization and orchestration experience using Docker and Kubernetes (AKS) is essential.

Requirements:

• Candidates must have 8+ years of relevant experience in Machine Learning, Data Engineering, or MLOps roles.
• A proven track record of building, deploying, and maintaining ML systems in production environments is mandatory.
• Proficiency with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn is required.
• Hands-on experience with MLflow, SageMaker, and Azure ML for model training, tracking, and deployment is essential.
• Candidates should be skilled in CI/CD pipelines for ML using GitHub Actions, Azure DevOps, and Terraform.
• Expertise in model observability, monitoring, and drift detection is necessary.
• Experience building and managing ML pipelines using Airflow, Azure Data Factory, and related tools is required.
• Cloud infrastructure expertise with Azure (primary) and AWS (secondary) is mandatory.
• Containerization and orchestration experience using Docker and Kubernetes (AKS) is essential.

Benefits:

• Health Insurance is provided because health comes first.
• Flexible working hours are available to accommodate personal schedules.
• Open holidays allow employees to take the time they need for themselves.
• Profit distribution is offered for everyone in the company.
• Mindera Annual Trip, Sports, and sharing groups are organized to connect and have fun.
• Training and conferences are supported, allowing employees to create their own training plans.
• Child Care vouchers are provided to assist with family needs.
• Employees can choose their own Laptop & Peripherals that best suit their needs.
• A hotspot with unlimited usage (PT) is available for work or personal use.
• Amazing offices are located in Porto, Aveiro, and Coimbra, with remote work options from Portugal and other countries depending on location and projects.
• A wide range of snacks is available at the offices to keep employees fed and healthy.
• Partnerships with local businesses are established for additional benefits.