🛠 Tech Stack

💼 About This Role

You'll architect and lead the infrastructure strategy for a next-generation Production ML platform on Google Cloud. You'll build the paved road for engineers, automating everything from model deployment to complex networking perimeters. This high-trust, outcome-focused team solves challenging ML problems at scale.

🎯 What You'll Do

• Design and maintain elastic cloud infrastructure (GCP) and Kubernetes for ML workloads.
• Build CI/CD pipelines for training, testing, and deploying ML models.
• Implement observability for model drift, latency, and performance degradation.
• Bridge data engineers, ML engineers, and backend/frontend teams for smooth production operations.

📋 Requirements

• 8-10+ years in DevOps/Platform Engineering.
• 2+ years operating production ML workloads.
• Deep GCP and GKE expertise (VPC-SC, IAM, Helm, Kustomize, ArgoCD).
• Expert-level Terraform with GitOps workflow.

✨ Nice to Have

• ML Observability experience (model accuracy monitoring, data/concept drift).
• Automation Savvy with Ansible.
• Kubernetes CKA/CKS or GCP certifications.

🎁 Benefits & Perks

• 🚀 Solve real customer problems at a scrappy, nimble organization.
• 👁️ See your impact every day in a high-trust environment.
• 📈 Accelerate your career with opportunities to learn new technologies.
• 🤝 Work with talented people at a company where people matter.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min
4. 4Offer· 30 min