🛠 Tech Stack

💼 About This Role

You'll design and build scalable systems for AI/ML infrastructure at a company redefining manufacturing through intelligent automation. Your core impact is enabling computer vision models for defect detection in real-world factory conditions. This role offers the chance to work with GPU workloads in Kubernetes on a platform powering the factory of the future.

🎯 What You'll Do

• Design and maintain scalable infrastructure for ML/AI pipelines
• Write clean code and perform peer code reviews
• Prototype new technology and evaluate technical feasibility
• Collaborate with teams to improve frameworks and developer velocity

📋 Requirements

• 5+ years in Platform Engineering, DevOps, or SRE
• Proficiency in Python or similar modern programming language
• Demonstrated MLOps industry best practices
• Strong knowledge of Kubernetes and modern k8s paradigms

✨ Nice to Have

• Experience in air-gapped or strict security environments
• Experience communicating with users and technical leaders
• Ability to mentor and grow other team members

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter phone screen· 30 min
2. 2Technical interview· 60 min
3. 3Hiring manager interview· 45 min