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AI Platform Reliability Engineer

Evan Ferrari

Full-time · Job · New_York

About the role

We serve inference workloads for over 300 model-serving customers who expect five-nines reliability from our GPU fleet. You'll join a cross-functional squad with defined sprints, clear ownership, and weekly syncs with leadership. This role focuses specifically on the reliability side: incident response, capacity planning, and reducing the operational load on the on-call rotation, working from our New York office alongside the infrastructure team.

Responsibilities

  • Own incident response for GPU fleet reliability issues
  • Build capacity planning tools for inference workload forecasting
  • Reduce operational toil for the on-call rotation
  • Maintain monitoring dashboards for platform health
  • Run blameless postmortems after significant incidents

Requirements

  • 3+ years in site reliability or infrastructure engineering
  • Strong hands-on experience with Kubernetes and Docker
  • Familiarity with AWS and GCP infrastructure
  • Experience with MLflow or similar ML tooling is a plus
  • Comfortable working on-site from our New York office

Benefits

  • On-site role, New York office
  • Competitive salary
  • Health and dental insurance
  • 401k matching
  • Free daily lunch

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Categories

MLOps & AI Infrastructure

Skills

kubernetes docker aws gcp mlflow

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Language

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Salary Range

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AI Expertise

MLOps & AI Infrastructure

Skills

kubernetes docker aws gcp mlflow

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