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AI Capacity Forecasting Reliability Engineer

Ulvex Systems

Remote · $160k – $200k / year · Full-time · Posted 3 months ago

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About the role

Our mission is to make sure nobody gets paged for a capacity problem we could have predicted. This role sits inside that mission directly: you'll build the forecasting layer that predicts when a service is heading toward resource exhaustion, days before it becomes an incident. We don't care where you work from. We care about clear async updates, ownership of what you ship, and whether the forecasts you build actually prevent pages instead of adding more noise to an already busy on-call channel. You'll pull from log pattern mining and anomaly detection work the observability team has already built, extending it with capacity trend models that feed into our existing alerting pipeline.

Fully remote.

Responsibilities

  • Build capacity forecasting models for compute, memory, and queue depth trends
  • Integrate forecasts into the existing alerting and on-call pipeline
  • Reduce false-positive alert volume through better trend confidence scoring
  • Partner asynchronously with the observability team on shared data sources
  • Document forecasting assumptions clearly for on-call engineers to trust the alerts

Requirements

  • Experience with time-series forecasting applied to infrastructure metrics
  • Comfortable with Spark or Kafka for streaming metric pipelines
  • Familiarity with Kubernetes-based service architectures
  • Strong written communication for async, distributed teams

Benefits

  • Fully async, work from anywhere
  • Unlimited PTO with a mandatory two-week minimum
  • Home office stipend
  • Health coverage regardless of country of residence
  • No mandatory meetings before 11am in your local time zone

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python sql spark kafka airflow kubernetes statistics

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