🛠 Tech Stack

💼 About This Role

You'll design, deploy, and maintain the ML infrastructure backbone for frontier AI research at a team behind Latent Diffusion and Stable Diffusion. Your work directly impacts multi-week training runs and production inference. We offer a collaborative, low-ego culture with real offices in Freiburg and SF.

🎯 What You'll Do

• Design and deploy cloud-based ML training clusters (Slurm) and inference clusters (Kubernetes)
• Manage network-based cloud file systems and blob/S3 storage for ML workloads
• Develop and maintain Infrastructure as Code (IaC) for resource provisioning
• Implement CI/CD pipelines for ML workflows and custom autoscaling solutions

📋 Requirements

• Strong proficiency in cloud platforms (AWS, Azure, or GCP) with ML/AI services
• Extensive experience with Kubernetes and Slurm in production environments
• Expertise in Infrastructure as Code tools (Terraform, Ansible)
• Proven track record managing network-based cloud file systems and object storage for ML

✨ Nice to Have

• Experience building custom autoscaling solutions for ML workloads
• Knowledge of cost optimization strategies for cloud-based ML infrastructure
• Familiarity with MLOps practices and tools

🎁 Benefits & Perks

• 🏢 Full-time in-person collaboration with offices in Freiburg and SF
• 🏖️ Monthly in-person week for remote team members, with travel covered
• 💰 Base annual salary $180,000–$300,000 USD
• ⚛️ Frontier AI research with open science values

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3On-site / Final Round· 3-4 hours