Senior Machine Learning Operations

Detalhes da Vaga

Job Title: Senior Machine Learning Operations (MLOps) Location: Preferably Hybrid in Porto Work Regime: Full-time Overview / Summary: LUZA Group is looking for a Senior MLOps Engineer to join our team.
This role will focus on managing, monitoring, and optimizing machine learning workflows in production, ensuring automation, scalability, and seamless integration of code and models into production environments.
Responsibilities and Tasks: Manage, monitor, and optimize the end-to-end machine learning workflows in production environments.
Automate and scale machine learning pipelines, ensuring they are reliable, efficient, and performant.
Work closely with data scientists and engineers to integrate machine learning models into production systems.
Ensure the continuous integration and deployment (CI/CD) of machine learning code and models across various environments.
Troubleshoot and resolve issues related to model deployment, performance, and scalability.
Monitor model performance and ensure that models are running efficiently in production, implementing improvements as needed.
Mandatory Requirements: Extensive experience in MLOps or DevOps with a focus on machine learning workflows.
Proficiency with tools such as Azure ML , Docker , Kubernetes , and CI/CD pipelines tailored for machine learning.
Strong experience in Python and machine learning libraries like scikit-learn , TensorFlow , KubeFlow , etc.
Solid understanding of cloud platforms , particularly Azure .
Experience in deploying and maintaining machine learning models in production environments at scale.
Languages: Portuguese and English, both fluent.
Nice to have: Microsoft Certified: Azure Machine Learning or Azure DevOps Engineer certification.
Familiarity with version control systems (e.g., Git ) and infrastructure-as-code tools (e.g., Terraform ).
Experience with monitoring and logging tools to track model performance and system health (e.g., Prometheus , Grafana ).
Knowledge of cloud-native architectures and container orchestration tools like Kubernetes .


Salário Nominal: A acordar

Fonte: Talent_Dynamic-Ppc

Função de trabalho:

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