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AI Deployment Rollback Time Predictor

Mia Levy

Full-time · Job · Chicago

About the role

Docker, Kubernetes, and MLflow are the core of what we build for clients running dozens of models in production simultaneously. In this role, you'll build the model that predicts how long a rollback will take given deployment size and dependency graph complexity, so on-call engineers can make faster go/no-go decisions during incidents. Expected impact: cutting average incident resolution time for our clients' ML platforms by giving their teams an accurate estimate before they commit to a rollback path.

Responsibilities

  • Build models predicting rollback duration from deployment metadata
  • Integrate predictions into existing deployment tooling
  • Analyze historical rollback logs to identify duration drivers
  • Partner with platform engineers on tooling integration
  • Validate predictions against real incident outcomes

Requirements

  • Experience with MLOps tooling, Docker and Kubernetes
  • Strong Python skills
  • Familiarity with MLflow or similar experiment tracking tools
  • Comfortable analyzing operational or incident data

Benefits

  • Remote position
  • Health, dental, vision insurance
  • Equity
  • Conference and training budget

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Categories

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python docker kubernetes mlflow aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python docker kubernetes mlflow aws

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