🛠 Tech Stack

💼 About This Role

You'll architect and lead the infrastructure strategy for a next-generation Production ML platform on Google Cloud. You will build the "paved road" for engineers, automating model deployment and complex networking. This role offers the chance to solve challenging problems in the ML space at a high-trust, outcome-focused company.

🎯 What You'll Do

• Design and maintain elastic scaling GCP infrastructure and Kubernetes clusters
• Build CI/CD pipelines for training, testing, and deploying ML models
• Implement observability tools for model drift, accuracy, and latency
• Collaborate with data, ML, backend, and frontend engineers

📋 Requirements

• 8-10+ years in DevOps/Platform Engineering with 2+ years in production ML workloads
• Deep hands-on experience with GCP (VPC-SC, IAM) and GKE (Helm, Kustomize, ArgoCD)
• Expert-level Terraform with GitOps/Atlantis workflow
• Experience with Istio, Kong, and identity/secrets management (Auth0, ESO)

✨ Nice to Have

• Experience with ML observability and data drift detection
• Ansible for cluster bootstrap and recovery
• Kubernetes (CKA/CKS) or GCP certifications

🎁 Benefits & Perks

• 🔬 Solve real customer problems
• 📈 See your impact in a nimble organization
• 🚀 Accelerate your career with growth opportunities
• 🤝 Work with talented people at a company that values inclusion

📨 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. 4Hiring manager· 45 min
5. 5Offer· 0 min