Remote GCP ML Platform Architect: Scale & Reliability

Wizdaa Inc.; Argentina; Remote; ARS 181,906,000 - 272,860,000; Full time

Job summary

Wizdaa Inc. seeks a Platform Architect to set the standard for ML and AI infrastructure at scale. You will bridge ML infrastructure and SRE, owning deployment pipelines, model serving reliability, and cost-aware multi-tenant orchestration on GKE.

You’ll champion IaC, Terraform, GitOps, and CI/CD for reproducible pipelines, with strong GCP experience and a focus on production-grade ML systems. Remote LATAM, USD payments, EST hours.

Qualifications

• 5+ years in platform engineering, SRE, MLOps, or infrastructure at scale.
• Hands-on experience deploying ML/AI workloads in production: serving, inference, or training.
• Strong SRE/DevOps foundation with measurable reliability improvements.
• Deep Terraform expertise with multi-project configurations and CI-driven workflows.
• GitOps in production (ArgoCD or Flux) with declarative infra management.
• Kubernetes production experience (GKE, with multi-tenant considerations) and cost awareness.
• Strong GCP background: VPC, Compute Engine, IAM, Cloud Storage; BigQuery production usage.
• Hands-on experience with CI/CD pipelines and ML pipelines (GitHub Actions, Cloud Build, etc.).
• Automation-first mindset; ability to reduce manual work and improve toil.
• Excellent communication to explain operational decisions and trade-offs.

Responsibilities

• Build and operate model and inference serving infrastructure for real-time and batch workloads.
• Own ML deployment lifecycle: registry, versioning, promotion, canary/shadow rollout, rollbacks.
• Manage agentic/LLM workloads, gateways, quotas, guardrails, and graceful degradation.
• Create reproducible ML pipelines as code, with lineage and reproducibility built in.
• Extend IaC to ML systems using Terraform patterns and multi-project design.
• Operate GitOps for ML workloads with ArgoCD across environments and tenants.
• Run ML workloads on multi-tenant Kubernetes (GKE) with GPU scheduling and tenancy isolation.
• Define SLOs for inference services and monitor data/model drift and incident response.
• Drive ML cost efficiency via right-sizing accelerators and cost attribution across tenants.
• Review agentic tooling outputs to multiply engineering productivity.

Skills

SRE/DevOps

MLOps

Kubernetes

GitOps

CI/CD

GCP

BigQuery

Dataflow

Vertex AI

GKE

Tools

Terraform

ArgoCD

Kubeflow

Cloud Build

GitHub Actions

Cloud Composer

Job description

Wizdaa Inc. seeks a Platform Architect to set the standard for ML and AI infrastructure at scale. You will bridge ML infrastructure and SRE, owning deployment pipelines, model serving reliability, and cost-aware multi-tenant orchestration on GKE.

You’ll champion IaC, Terraform, GitOps, and CI/CD for reproducible pipelines, with strong GCP experience and a focus on production-grade ML systems. Remote LATAM, USD payments, EST hours.