Senior MLOps Engineer: Cloud ML, GPU, CI/CD

Inetum; Viseu; Presencial; EUR 55 000 - 85 000; Tempo integral

Resumo da oferta

Inetum in Porto is seeking a Mid-Senior Machine Learning Operations Engineer to join the DLPP team. The role requires 5–8 years in MLOps, strong Python skills, and hands-on work with TensorFlow, PyTorch or Scikit-learn. You will implement CI/CD, ensure data security and privacy, and optimize cloud ML services on AWS/Azure/Google Cloud.

The ideal candidate is proactive, analytical, and collaborative. The position emphasizes collaboration, continuous improvement, and delivering reliable ML

Qualificações

• 5–8 years of experience in MLOps or a related field.
• Proven ability to ensure security and data privacy compliance across all MLOps activities.
• Strong proficiency in Python and hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
• Solid understanding of CI/CD pipelines, automation tools, and version control systems (e.g., Git).
• Experience maintaining secure and reliable Data Science environments (vulnerabilities, obsolescence...).
• Hands-on experience with cloud platforms AWS, Azure, or Google Cloud and their ML services.
• Knowledge of GPU usage and management, including configuring and optimising GPU instances on cloud platforms and managing GPU drivers/libraries (CUDA, Nvidia).
• Strong analytical and organisational skills; proactive, pragmatic, curious, and autonomous approach to work.
• Excellent team spirit and interpersonal skills.
• Experience with Prometheus and Grafana for metrics and monitoring.
• Familiarity with containerisation and orchestration technologies.
• Knowledge of Infrastructure as Code and automation practices.

Conhecimentos

Python

TensorFlow

PyTorch

Scikit-learn

CI/CD

Git

MLOps

Data privacy

AWS

Azure

Google Cloud

GPU management

Prometheus

Grafana

Containers

Kubernetes

Infrastructure as Code

Ferramentas

Docker

Kubernetes

Prometheus

Grafana

CI/CD tools

Descrição da oferta de emprego

Inetum in Porto is seeking a Mid-Senior Machine Learning Operations Engineer to join the DLPP team. The role requires 5–8 years in MLOps, strong Python skills, and hands-on work with TensorFlow, PyTorch or Scikit-learn. You will implement CI/CD, ensure data security and privacy, and optimize cloud ML services on AWS/Azure/Google Cloud.

The ideal candidate is proactive, analytical, and collaborative. The position emphasizes collaboration, continuous improvement, and delivering reliable ML