🛠 Tech Stack

💼 About This Role

You'll architect the infrastructure strategy for a next-generation Production ML platform on Google Cloud. Your work will ensure elastic, secure, and resilient systems for high-performance ML workloads. You'll build the "paved road" for engineers, automating everything from model deployment to complex networking.

🎯 What You'll Do

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

📋 Requirements

• 8-10+ years in DevOps/Platform Engineering with 2+ years in production ML.
• Deep GCP and GKE experience (VPC-SC, IAM, Helm, ArgoCD, Istio).
• Expert-level Terraform skills with GitOps workflow.
• Experience with Airflow and ML-serving stack (Triton, MLflow).

✨ Nice to Have

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

🎁 Benefits & Perks

• 🧩 Solve real customer problems with direct impact.
• 🚀 Accelerate your career in a growth-oriented environment.
• 🤝 Collaborate 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