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AI Test Flake Prediction Engineer

Lillian Nguyen

Full-time · Job · New_York

About the role

Our QA platform already generates synthetic test data and tracks test coverage, but flaky tests still waste hours of engineering time every week across our client base. We're looking for someone to build a model that predicts which tests are likely to flake before they even run, based on historical execution patterns. You'll work with a small, senior QA infrastructure team that values shipping over process, and you'll have direct ownership over this feature from prototype to production rollout.

Responsibilities

  • Build models that predict flaky test behavior from historical run data
  • Integrate flake predictions into existing CI/CD test reporting
  • Work with MLflow to track model performance over time
  • Partner with client QA teams to validate prediction accuracy
  • Ship incremental improvements without waiting for a big-bang release

Requirements

  • 3+ years of experience with ML modeling in a software engineering context
  • Experience with scikit-learn and model tracking tools like MLflow
  • Familiarity with CI/CD systems and test infrastructure
  • Comfortable working with Docker and Kubernetes-based test environments
  • Track record of shipping production ML features independently

Benefits

  • Fully remote position
  • Competitive salary plus equity
  • Health insurance covered at 100%
  • Flexible working hours
  • Direct ownership over a high-impact QA feature

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Categories

MLOps & AI Infrastructure

Skills

python scikit-learn docker kubernetes mlflow

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python scikit-learn docker kubernetes mlflow

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