MLOps Engineer

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MidHybrydaFull-time

#445783·Dodano 26 dni temu·4

Źródło: IT Factory

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Tech Stack / Keywords

Azure Machine LearningAzure AI FoundryAKS Docker KubernetesDVCMLflow Python TerraformBicep

Firma i stanowisko

IT Factory is a dynamic company with experience in developing, deploying, and supporting IT solutions for a major Polish company in the insurance and financial industry.

Wymagania

Minimum 3 years of experience in DevOps, MLOps, or software engineering with production ML model experience
Advanced knowledge of Docker and Kubernetes (cluster management, Helm charts, Ingress)
Deep knowledge of Azure platform (especially Azure ML, AKS, Azure Container Registry) or GCP/AWS with readiness to quickly transition to Azure
Experience building CI/CD pipelines with Azure DevOps, GitHub Actions, or Jenkins tailored for ML workflows
Good knowledge of Python and Bash/Shell scripting
Practical experience with MLflow, Kubeflow, or native cloud model lifecycle management tools
Familiarity with infrastructure as code tools like Terraform, Bicep, or Ansible
Technical higher education in computer science, telecommunications, or related fields
Automation-first mindset to reduce manual work via scripts and tools
Ability to work at the intersection of Data Science and IT Operations teams
Proactive in resolving performance issues and production incidents
Providing services from the territory of Poland

Nice to have:

Azure certifications: DevOps Engineer Expert (AZ-400) or Azure AI Engineer (AI-102)
Experience deploying LLM models and RAG architectures
Familiarity with monitoring tools like Prometheus, Grafana, Azure Monitor
Understanding hybrid cloud networking (VPN, VNet, Private Endpoints)
Knowledge of vector databases (e.g. in context of Azure AI Search)

Obowiązki

Create and maintain AI platform infrastructure in the insurance domain
Design and build scalable MLOps/LLMOps infrastructure including Azure Machine Learning, Azure AI Foundry, and AKS
Implement CI/CD/CT pipelines for ML solutions with automated testing, data and model versioning using DVC and MLflow
Prepare Docker images for AI models and manage deployments on Kubernetes clusters in hybrid architecture
Deploy model monitoring for Data Drift/Model Drift, logging, and alerting to ensure high availability
Provide technical support for AI Act compliance including audit tools, data lineage, access management, and encryption
Optimize costs and performance by managing Azure resources and scaling infrastructure based on workload

Inne informacje

Provision of services from the territory of Poland is required.

IT Factory

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