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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading Machine Learning teams, driving technical vision, and managing the end-to-end lifecycle of production safety models. Proven ability to collaborate cross-functionally and deliver pragmatic solutions in complex environments.
Highest-signal resume keywords
Machine Learning EngineeringEngineering ManagementAbuse/Fraud DetectionContent ClassificationTeam Leadership
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData ScienceApplied ScienceBehavioral ModelingGraph-Based ModelingLLM-Based ClassificationProduction ML SystemsPerformance MeasurementOperational Health MonitoringTechnical Expertise
Soft Skills
Strong CommunicationProblem SolvingCollaborationCoachingFirst-Principles Thinking
Industry Keywords
Safety MLTrust & SafetyLabel QualityGolden SetsAutomated Investigations
About the role
Key responsibilities & impact- Build and lead an exceptional team of ML 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
- Manage processes and apply technical expertise to raise standards and ensure exceptional results
- Partner with Trust & Safety on label quality, golden sets, and automating manual investigations
- Collaborate with other Engineering Managers to improve the Engineering organization and uphold Discord’s workplace philosophy
Requirements
What you’ll need- 5+ years of experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist
- 3+ years of experience as an Engineering Manager
- Successfully managed a team of 5+ engineers
- Hands-on depth in at least one of: abuse/fraud detection, content classification, behavioral modeling, graph-based modeling, or LLM-based classification systems
- Strong communication skills and ability to work well cross-functionally
- Ability to thrive in ambiguous environments and solve complex problems
- First-principles thinking and ability to develop pragmatic solutions collaboratively
- Proven record of shipping ML systems to production at scale
- Passion for coaching and leading engineers while contributing hands-on to code
- Keeps up with industry trends and identifies technologies to solve technical problems
Benefits
Comp & perks- Equity
- Benefits
- Reasonable accommodations during the interview process