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AI Model Serving Autoscaling Cost Forecaster

David Dubois

Full-time · Job · Los_Angeles

About the role

The models you'll ship will directly decide how much every customer on our platform pays for inference next month, so accuracy here isn't optional. You'll build forecasting models that predict autoscaling costs ahead of traffic spikes, giving both our infra team and our customers early warning before a bill surprises anyone. This sits at the intersection of MLOps and FinOps, and you'll have real budget influence across the platform.

Responsibilities

  • Build cost forecasting models tied to real-time autoscaling signals
  • Own the pipeline connecting Kubernetes metrics to billing forecasts
  • Drive adoption of forecast-aware autoscaling policies
  • Partner with customer-facing teams on cost transparency tooling

Requirements

  • 7+ years in MLOps, platform engineering, or cost engineering
  • Deep Kubernetes and multi-cloud experience (GCP and AWS)
  • Track record building forecasting models in production
  • Comfortable owning infrastructure with direct financial impact

Benefits

  • Fully remote position
  • Top-of-market salary + equity
  • Health and dental insurance
  • Unlimited PTO

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Categories

MLOps & AI Infrastructure

Skills

python kubernetes docker gcp aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

MLOps & AI Infrastructure

Skills

python kubernetes docker gcp aws mlflow

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