Azure DevOps Engineer, ML Ops Engineer
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Job Description
Senior MLOps Engineer at Inallmedia, driving AI-driven automation in DevOps workflows. Collaborating with global teams to architect scalable cloud infrastructure and enhance system reliability.
Responsibilities:
- Drive AI-Driven Automation: Design, implement, and experiment with cutting-edge workflows that apply AI/LLMs to automate complex DevOps operations, reducing human intervention and operational friction.
- Architect Scalable Cloud Infrastructure: Oversee and optimize robust infrastructure solutions within Azure, ensuring top-tier performance, security, and monitoring.
- Define CI/CD & IaC Strategy: Champion best-in-class Infrastructure as Code (IaC) and continuous integration/deployment strategies to enable seamless, reliable software delivery.
- Act as a Strategic Technical Advisor: Influence architectural decisions and system design without needing direct authority, fostering a strong culture of research and innovation.
- Enhance System Reliability & Observability: Participate in deep architectural reviews, code reviews, and system design sessions to ensure high availability and cost-efficiency.
Requirements:
- 7+ years of experience in DevOps, Cloud Engineering, or Infrastructure architecture.
- Deep Azure Expertise: Proven mastery of Azure services, specifically Azure Kubernetes Service (AKS), cloud networking, compute, and native monitoring tools.
- Advanced Infrastructure as Code (IaC): Deep hands-on experience using Terraform, Bicep, or ARM templates.
- Robust Automation & Scripting: Strong programming proficiency in Python, Bash, or PowerShell to build custom automation tooling.
- AI/LLM Integration: Genuine, practical experience applying Large Language Models (LLMs) or AI tools to optimize real-world DevOps workflows.
- CI/CD Mastery: Solid background managing enterprise pipelines with GitHub Actions or Jenkins.
- English fluency for daily communication.
Benefits:
- Flexible work arrangements
- Professional development
- Remote work options
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