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AI Model Drift Detection Engineer

Lumio Systems

Remote · $130k – $160k / year · Full-time · Posted 4 months ago

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About the role

Our clients deploy models in production and forget about them — until something goes wrong. Lumio Systems builds the monitoring layer that catches model drift, data quality degradation, and performance regression before they become incidents. We're a team of 18 engineers with a clear product vision and strong enterprise traction. In this role, you'll own the drift detection framework. That means designing statistical tests for input distribution shift, building model performance tracking pipelines, and developing the alerting logic that tells an MLOps team exactly which feature dimension is drifting and how fast. You'll work across a diverse model portfolio — tabular classifiers, embedding models, time series forecasters, and LLM-backed pipelines. This is an infrastructure-heavy role that requires solid engineering discipline: your drift detection pipelines need to be reliable, low-latency, and explainable. You'll collaborate closely with clients' ML teams during onboarding and with our product team to shape the roadmap. Senior ownership from day one.

Fully remote.

Responsibilities

  • Design statistical tests and algorithms for feature and label distribution drift detection
  • Build model performance tracking pipelines across model types (tabular, LLM, time series)
  • Develop alerting and diagnostic dashboards for MLOps teams
  • Own the SDK that client ML engineers integrate into their deployment pipelines
  • Partner with product to define drift detection SLAs and roadmap features

Requirements

  • 5+ years ML engineering or MLOps experience
  • Strong understanding of statistical drift detection methods (PSI, KS, CUSUM)
  • Proficiency in Python, MLflow, and Kubernetes
  • Experience supporting production ML deployments at scale
  • Ability to explain technical findings to non-ML engineering audiences

Benefits

  • Remote-first culture
  • Equity in a fast-growing MLOps company
  • Health, dental, and vision coverage
  • $3,000 annual conference and training budget
  • Home office allowance ($2,000)

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Categories

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python mlflow airflow docker kubernetes

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python mlflow airflow docker kubernetes

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