IT Factory

MLOps Engineer

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MidHybryda·WarszawaInne·B2B

#445940·Dodano miesiąc temu·2

Źródło: justjoin.it

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Tech Stack / Keywords

Docker Kubernetes Azure CI/CD Python Shell Terraform

Podsumowanie oferty

The MLOps Engineer will work on creating and maintaining an AI platform within the insurance sector. The role involves designing and building scalable MLOps/LLMOps infrastructure on Azure, implementing CI/CD/CT pipelines for ML solutions, and managing deployment with Docker and Kubernetes in a hybrid architecture. Key responsibilities include monitoring AI models and ensuring compliance with AI Act requirements.

Wymagania

Minimum 3 years of experience in DevOps, MLOps, or software engineering, including production experience with ML models
Advanced knowledge of Docker and Kubernetes (cluster management, Helm charts, Ingress)
Deep knowledge of Azure (especially Azure ML, AKS, Azure Container Registry) or GCP/AWS with readiness to quickly adopt Azure
Experience building CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) with ML specifics (e.g., model training as a pipeline step)
Good knowledge of Python (working with ML tool SDKs) and Bash/Shell scripting
Practical experience with MLflow, Kubeflow, or native cloud solutions for model lifecycle management
Knowledge of Terraform, Bicep, or Ansible
Higher technical education (computer science, telecommunications, or related)
"Automation First" approach aiming to eliminate manual work via scripts and tools
Ability to work at the intersection of Data Science and IT Operations teams
Proactivity in resolving performance issues and production incidents
Service provision limited to 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
Knowledge of monitoring tools (Prometheus, Grafana, Azure Monitor)
Understanding of networking concepts in hybrid cloud (VPN, VNet, Private Endpoints)
Knowledge of vector databases (e.g., in context of Azure AI Search)

Obowiązki

Creating and maintaining an AI platform in the insurance industry
Designing and building MLOps/LLMOps infrastructure: scalable environment for training and serving models (including Azure Machine Learning, Azure AI Foundry, AKS)
Implementing CI/CD/CT pipelines for ML solutions, including automatic testing, data and model versioning (DVC, MLflow), continuous training
Preparing Docker images for AI/GenAI models and managing their deployments on Kubernetes clusters with hybrid architecture (integration with on-premise systems)
Implementing model monitoring (detecting Data Drift/Model Drift), logging, and alerting to ensure high availability of AI services
Providing technical support for compliance with AI Act: tools for model auditability, data lineage, and security (access management, encryption)
Optimizing costs and performance: managing Azure resources, optimizing model inference time, scaling infrastructure based on load

Inne informacje

Service provision limited to the territory of Poland.

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