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AI Deployment Freeze Window Scheduler

Nathan Yamamoto

Full-time · Job · Denver

About the role

We just closed our Series A and are scaling fast, which means the number of teams pushing model updates every week has tripled — and so has the risk of two releases colliding badly. We need a senior engineer to build the scheduling layer that coordinates freeze windows across teams, blocks risky overlapping deployments, and gives release managers a single source of truth for what's going out and when. You'll have direct input into how our entire deployment platform evolves over the next year.

Responsibilities

  • Build scheduling and conflict-detection logic across deployment pipelines
  • Own the freeze-window policy engine end to end
  • Coordinate with platform teams to integrate with existing CI/CD
  • Reduce deployment collisions and rollback incidents

Requirements

  • 6+ years in MLOps or infrastructure engineering
  • Deep experience with Kubernetes and CI/CD orchestration
  • Comfortable owning a system with company-wide visibility
  • Prior experience at a fast-scaling startup a plus

Benefits

  • Fully remote position
  • Competitive salary + meaningful equity
  • Health and dental insurance
  • Home office stipend

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Categories

MLOps & AI Infrastructure

Skills

python kubernetes docker airflow aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python kubernetes docker airflow aws mlflow

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