🛠 Tech Stack

💼 About This Role

You'll design and automate enterprise-grade AWS SageMaker environments and MLOps/DevOps solutions for an innovative tech company. Your work will directly enable data science teams to deploy ML models faster and more reliably in a remote-first international setting.

🎯 What You'll Do

• Design and automate AWS SageMaker infrastructure solutions.
• Build CI/CD pipelines for Docker-based ML workloads.
• Implement monitoring, alerting, and cost controls for SageMaker.
• Support MLOps initiatives automating model deployments.

📋 Requirements

• 6+ years of experience in DevOps or Cloud Engineering.
• Expert-level knowledge of AWS services and Python.
• Hands-on experience with AWS SageMaker and ML infrastructure.
• Experience building enterprise-scale CI/CD pipelines.

✨ Nice to Have

• Familiarity with Docker and containerized environments.
• Experience with MLOps and model deployment automation.
• Knowledge of Jenkins or similar CI/CD tools.

🎁 Benefits & Perks

• 🏖️ Remote-first work across Europe
• 🔬 Cutting-edge AI/ML projects
• 💼 Flexible employment (Contractor or Full-time)
• 🌍 International team with strong engineering culture
• 📈 Career growth in cloud and AI technologies

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

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