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Engineering Manager, Machine Learning

Leads Discord’s Safety ML team, setting technical direction and overseeing production machine learning systems for content understanding, account integrity, and platform abuse. Requires substantial machine learning and engineering management experience, hands-on technical depth, and experience delivering ML systems at scale.

About the job

Responsibilities

  • Build and lead a team of machine learning engineers through hiring, coaching, and fostering ownership and impact.
  • Drive the technical vision and roadmap for Safety ML in collaboration with Trust & Safety, Product, Policy, Legal, and Data Science.
  • Own the end-to-end lifecycle of production safety models, including defining capabilities, measuring performance, and monitoring operational health.
  • Improve processes and apply technical expertise to raise engineering quality and delivery standards.
  • Partner with Trust & Safety on label quality, golden sets, and automating manual investigations.
  • Collaborate with other Engineering Managers to improve the Engineering organization.

Requirements

  • 5+ years of experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist.
  • 3+ years of experience as an Engineering Manager managing a team of 5+ engineers.
  • Hands-on experience with abuse or fraud detection, content classification, behavioral modeling, graph-based modeling, or LLM-based classification systems.
  • Strong communication and cross-functional collaboration skills.
  • Experience shipping machine learning systems to production at scale.
  • Passion for coaching and leading engineers while remaining hands-on with code.
  • Ability to solve complex problems in ambiguous environments and apply pragmatic, first-principles thinking.
  • Ability to keep up with industry trends and identify useful technologies.

Compensation

  • US base salary: $272,000-$306,000, plus equity and benefits.

Skills

Machine Learning, Data Science, Abuse Detection, Fraud Detection, Content Classification, Behavioral Modeling, Graph-Based Modeling, LLMs, Python, Production Ml Systems

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