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AI Network Intrusion Pattern Analyst

Eliana Magnusson

Full-time · Job · New_York

About the role

Network traffic data is a firehose — 4 billion flow records per day across our client deployments. Somewhere in that torrent are the 200 flows that represent an active intrusion: lateral movement, data exfiltration, command-and-control communication. Finding those 200 flows without generating 10,000 false alerts is the problem we solve. The detection models use graph-based features (communication patterns between hosts), temporal features (activity at unusual hours or durations), and content features (protocol anomalies, payload characteristics). You'll improve detection by building better graph representations of network behavior, designing features that capture attacker tradecraft patterns, and reducing the false positive rate that currently drives alert fatigue in our client SOCs. The threat detection team is six engineers. You'll focus on the feature engineering and model development side while others handle data ingestion and alert delivery. Every model change gets tested against a red team dataset — our own security researchers generate realistic attack traffic to benchmark detection accuracy.

Responsibilities

  • Build graph-based features capturing network communication patterns
  • Design temporal and behavioral features for intrusion detection models
  • Reduce false positive rates while maintaining detection sensitivity
  • Evaluate models against red team attack simulations
  • Analyze missed detections to identify feature gaps
  • Collaborate with threat intelligence analysts on emerging attack patterns

Requirements

  • 3+ years in ML engineering with network security or anomaly detection experience
  • Experience with graph-based features and network flow data
  • Strong Python and distributed computing skills for large-scale data
  • Understanding of network protocols and common attack techniques
  • Ability to work with security operations teams on detection requirements

Benefits

  • Fully remote with quarterly team meetings
  • Competitive salary plus performance bonus
  • Comprehensive health coverage
  • $3,500 annual conference and training budget
  • Access to proprietary threat intelligence datasets

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch sql spark docker

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch sql spark docker statistics

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