GCP AI/MLOps Platform Engineer

We are looking for an experienced

GCP AI/MLOps Platform Engineer

to design, build, and operate scalable, secure, and reliable cloud infrastructure for AI/ML and application workloads. You will work closely with Data Scientists and ML Engineers to productionize models and automate the end-to-end ML lifecycle.

Key Responsibilities

• Design and manage scalable GCP infrastructure using

Vertex AI, GKE, Cloud Run, BigQuery, IAM, and VPC

.

• Build CI/CD and MLOps pipelines for model training, deployment, monitoring, and rollback.
• Implement

Terraform-based Infrastructure as Code

and cloud automation.

• Containerize and orchestrate workloads using

Docker and Kubernetes/GKE

.

• Establish monitoring, logging, alerting, and observability using

Cloud Monitoring, Prometheus, and Grafana

.

• Implement cloud security, IAM, secrets management, and compliance best practices.
• Troubleshoot production issues and drive automation, reliability, and cost optimization.
• Collaborate with AI/ML teams to streamline the journey from experimentation to production.

Required Skills

• 7+ years

in Platform Engineering, DevOps, Cloud, or Infrastructure Engineering.

• Strong hands-on experience with

GCP, Vertex AI, GKE, Cloud Run, BigQuery, IAM, and networking

.

• Strong CI/CD experience with

Cloud Build, GitHub Actions, Jenkins, GitLab CI, or ArgoCD

.

• Expertise in

Terraform, Docker, Kubernetes, Python/Bash/Go

.

• Strong understanding of

MLOps and ML lifecycle management

.

• Experience with

MLflow/Kubeflow, monitoring, observability, and cloud security

.

Preferred

• GCP Professional certification(s).
• Experience with

Generative AI/LLM platforms, Gemini, or Vertex AI Model Garden

.

• Experience with

GitOps, ArgoCD/Flux, enterprise environments, and FinOps

.