MLOps Platform Engineer - AI Reliability & Scale

Verisure Sàrl
Ourense, Spain
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
€ 70K

Job location

Ourense, Spain

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Continuous Integration
Github
Python
Prometheus
Large Language Models
Grafana
Kubernetes
Machine Learning Operations
Terraform
Docker

Job description

Verisure in Galicia is seeking an MLOps / AIOps Engineer to design and manage our AIOps platform, ensuring operational efficiency and reliability of AI products. This role emphasizes platform engineering, infrastructure management, and automation using AWS and Azure technologies., * Design, maintain, and evolve the AIOps platform.

  • Build and operate ML and LLM pipelines with reliability and observability.
  • Implement LLMOps practices including evaluation and observability.
  • Ensure continuous operation of AI products.
  • Manage deployments in cloud environments.
  • Collaborate with Data Scientists and Data Engineers.
  • Contribute to internal standards and practices.

Conocimientos

MLOps experience LLMOps knowledge AWS experience Azure knowledge Docker/Kubernetes knowledge CI/CD experience Observability tools familiarity Infrastructure as code Python experience ML lifecycle understanding

Herramientas

Terraform GitHub Actions Prometheus MLflow SageMaker Descripción del empleo

Requirements

The ideal candidate should possess substantial experience in MLOps and solid knowledge of LLMOps, alongside a collaborative mindset to work effectively with our multidisciplinary Data & AI team., * Hands-on experience in MLOps, AIOps, or operating ML systems in production.

  • Solid understanding of LLMOps and AgentOps concepts.
  • Experience working with AWS and/or Azure in production environments.
  • Practical knowledge of containers and Kubernetes.
  • Experience with CI/CD pipelines.
  • Familiarity with observability and monitoring concepts.
  • Experience managing infrastructure as code.
  • Python experience and familiarity with the ML ecosystem.
  • Good understanding of the ML / LLM lifecycle.
  • Fluent English to work in an international environment., The ideal candidate should possess substantial experience in MLOps and solid knowledge of LLMOps, alongside a collaborative mindset to work effectively with our multidisciplinary Data & AI team. Consigue la evaluación confidencial y gratuita de tu currículum

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