🛠 Tech Stack

💼 About This Role

You'll build and optimize MLOps and DevOps solutions for AWS SageMaker environments in an innovative, fast-paced tech company. Your work will automate machine learning workflows, streamline deployments, and enable data science teams to move faster and more reliably across complex AI ecosystems.

🎯 What You'll Do

• Design and automate enterprise-grade AWS SageMaker environments and infrastructure
• Develop DevOps automation frameworks for scalable ML operations
• Build and manage CI/CD pipelines for ML workloads
• Create monitoring, alerting, and cost-control mechanisms for SageMaker

📋 Requirements

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

✨ Nice to Have

• Experience with Jenkins for deployment pipelines
• Familiarity with Docker and containerized environments
• Experience with MLOps practices and model deployment automation

🎁 Benefits & Perks

• 🌍 Remote-first work environment across Europe
• 💡 Cutting-edge AI, cloud, and MLOps projects
• 🔄 Flexible employment options (Contractor or Full-time)
• 📈 Career growth opportunities in advanced cloud and AI technologies
• 🤝 Collaborative and innovation-driven engineering culture

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager· 45 min