🛠 Tech Stack

💼 About This Role

You'll design and automate AWS SageMaker environments for enterprise-scale MLOps and DevOps solutions. You'll enable data science teams with scalable CI/CD pipelines and infrastructure automation. This role offers strong ownership of cutting-edge AI and cloud initiatives.

🎯 What You'll Do

• Design and automate AWS SageMaker environments and infrastructure
• Develop DevOps automation for scalable MLOps
• Configure SageMaker lifecycle policies for ML teams
• Build and manage CI/CD pipelines for Docker images and ML workloads
• Create monitoring, alerting, and cost-control for SageMaker

📋 Requirements

• 6+ years experience in DevOps, Cloud Engineering, or MLOps
• Expert-level knowledge of AWS services
• Strong proficiency in Python
• Hands-on experience with AWS SageMaker and ML infrastructure

✨ Nice to Have

• Experience with Jenkins pipeline creation
• Familiarity with Docker and containerized environments
• Exposure to MLOps practices and model deployment automation

🎁 Benefits & Perks

• 🏢 Remote-first work environment across Europe
• 🤖 Cutting-edge AI and cloud projects
• 💼 Flexible employment (Contractor or Full-time)
• 🌍 International team collaboration
• 🚀 Career growth in advanced cloud and AI technologies

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Team Fit Interview· 45 min