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AI Deployment Cost Attribution Engineer

Mia Levy

Contract · Job · Los_Angeles

About the role

Have you ever wondered why two deployments running the same model cost wildly different amounts per request? We run model deployments across dozens of services on GCP and Kubernetes, and right now nobody can say with confidence which team or feature is driving a given month's infrastructure bill. You'll join a squad with defined sprints and clear ownership, working closely with the platform team to build cost attribution tooling that maps spend back to specific models, teams, and endpoints — turning a vague monthly invoice into a dashboard finance and engineering both trust.

Responsibilities

  • Build cost attribution tooling mapping cloud spend to models and teams
  • Integrate attribution data into existing Kubernetes deployment pipelines
  • Partner with finance to define reporting requirements
  • Document attribution methodology for engineering and finance stakeholders

Requirements

  • 5+ years in infrastructure engineering with GCP and Kubernetes
  • Experience building cost or usage attribution tooling
  • Comfortable working independently on a fixed-term contract

Benefits

  • Competitive contract rate with possible extension
  • Fully remote, flexible working hours
  • Direct collaboration with senior reliability engineers

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Categories

MLOps & AI Infrastructure

Skills

kubernetes docker gcp mlflow

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Job Type

Contract

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure

Skills

kubernetes docker gcp mlflow

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