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AI Anomaly Detection Engineer

Aubrey Okafor

Full-time · Job · New_York

About the role

Telecom networks generate 50 billion events per day. Hidden in that noise are the signals that predict outages, security breaches, and capacity exhaustion — hours before they affect customers. Our anomaly detection platform processes these event streams in real-time and surfaces the 200 events per day that actually matter. You'll build the detection models: unsupervised anomaly detection for network telemetry, supervised classifiers for known failure patterns, and the meta-learning system that adapts detection thresholds across network topologies without manual tuning. The signal-to-noise ratio is extreme — one meaningful anomaly per 250 million normal events. False positives in telecom trigger expensive investigation workflows. False negatives mean outages. The cost asymmetry demands detection systems with surgical precision, and the data volumes demand architectures that process at wire speed. If you've worked at the intersection of ML and high-throughput systems, this problem will challenge you.

Responsibilities

  • Build unsupervised anomaly detection for real-time network telemetry streams
  • Design supervised classifiers for known telecom failure pattern recognition
  • Develop meta-learning systems for adaptive threshold tuning across network topologies
  • Optimize detection precision to minimize expensive false positive investigations
  • Scale detection infrastructure for 50 billion daily events processing

Requirements

  • 5+ years in anomaly detection or ML for time series data
  • Strong PyTorch and scikit-learn skills for detection modeling
  • Experience with high-throughput data processing systems
  • Deep understanding of precision-recall tradeoffs in imbalanced settings
  • Statistical expertise for threshold calibration and drift detection

Benefits

  • Fully remote — US East Coast hours
  • Senior compensation with equity
  • $3,000 annual learning budget
  • Impact on network reliability for millions of subscribers

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch scikit-learn sql pandas

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch scikit-learn sql pandas statistics docker

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