Senior MLOps Engineer - Scalable GCP AI Infra

Point Wild; Polska; Hybrid; PLN 240,000 - 360,000; Full time

Job summary

Point Wild seeks a Senior MLOps Engineer to design, build, and maintain production ML infrastructure on Google Cloud Platform. You will collaborate with AI researchers, data engineers, and backend teams to deploy, scale, and monitor models in production.

You will own ML CI/CD pipelines, observability, and reproducible training/deployment workflows using Vertex AI, GKE, Terraform, and related tools.

Qualifications

• At least 5 years of hands-on production ML in cloud environments.

Responsibilities

• Architect and manage scalable GCP-based ML infrastructure (Vertex AI, GKE, GCS, Cloud Run).
• Own end-to-end model deployment lifecycle and low-latency inference services.
• Build automated pipelines for training, testing, evaluation, and deployment (Airflow, Vertex AI Pipelines, GitHub Actions).
• Implement robust production observability for ML metrics and data drift to trigger retraining.
• Provide scalable training environments and standardized deployment templates for AI engineers.
• Collaborate with Data Engineers on feature stores, datasets, and data processing workflows.
• Lead the transition of PoCs to production microservices.

Skills

MLOps

GCP

Model serving

CI/CD

IaC

Python

Monitoring

Tools

Docker

Kubernetes/GKE

Vertex AI

MLflow

Airflow

Terraform

Job description

Point Wild seeks a Senior MLOps Engineer to design, build, and maintain production ML infrastructure on Google Cloud Platform. You will collaborate with AI researchers, data engineers, and backend teams to deploy, scale, and monitor models in production.

You will own ML CI/CD pipelines, observability, and reproducible training/deployment workflows using Vertex AI, GKE, Terraform, and related tools.