Principal Platform Engineer

Tasks

• Architect cloud infrastructure for production machine learning
• Build maintain CI CD pipelines for ML model training testing and deployment
• Collaborate with data ML backend and frontend engineering teams
• Design deploy and maintain elastic scaling infrastructure
• Implement Infrastructure as Code for scalable deployments
• Implement model monitoring for drift accuracy latency and performance
• Lead infrastructure strategy for machine learning workloads
• Manage Kubernetes clusters for high performance ML
• Operate on call for production systems
• Set up observability for system health and ML specific metrics

Perks/Benefits

• N/A

Skills/Tech-stack

Apache Airflow | Argo CD | Argo Workflows | Auth0 | BigQuery | ClickHouse | Cloud SQL | Cloud platform | Dex | Elasticsearch | GCP VPC | GCP VPC Service Controls | GitHub Actions | GitOps | Google Cloud | Google Cloud Platform | Google Kubernetes | Google Kubernetes Engine | Helm | IAM | Inference Server | Istio | Istio VirtualServices | Jenkins | Kong | Kubernetes | Kubernetes Engine | Kustomize | MLflow | MTLS | Machine Learning | NVIDIA Triton | NVIDIA Triton Inference | NVIDIA Triton Inference Server | Organization Policies | PostgreSQL | Python | SOPs | Service Controls | Terraform | Triton Inference Server | VLLM | VPC | VPC Service Controls