🛠 Tech Stack

💼 About This Role

You'll build and optimize scalable MLOps and DevOps solutions focused on AWS SageMaker environments. You'll collaborate with cross-functional teams to automate machine learning workflows and improve operational efficiency across complex AI ecosystems. This role offers strong ownership and exposure to advanced cloud technologies.

🎯 What You'll Do

• Design and automate AWS SageMaker environments and infrastructure.
• Develop DevOps automation frameworks for scalable MLOps.
• Build and manage CI/CD pipelines for Docker images and ML workloads.
• Create monitoring, alerting, and cost-control for SageMaker services.
• Support MLOps initiatives by automating model deployment processes.

📋 Requirements

• 6+ years in DevOps, Cloud Engineering, or MLOps roles.
• 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 or similar CI/CD tools.
• 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 and MLOps projects
• 🔄 Flexible employment options (Contractor or Full-time)
• 🌍 International and diverse team
• 📈 Career growth opportunities in cloud and AI technologies

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min
4. 4Offer· N/A