Engineering Manager, Safety ML - Lead Real-Time ML (Remote)

Mosaec; San Francisco (CA); Remote; USD 272,000 - 340,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Discord is seeking a hands‑on Engineering Manager for the Safety ML team in the US. You will own detection systems for content understanding, account integrity, and platform abuse at scale, guiding both real‑time and batch models.

You will hire, coach, and empower a high‑performing ML engineering group while coordinating with Trust & Safety, Product, Policy, Legal, and Data Science peers. You will drive the end‑to‑end lifecycle of production safety models, define new capabilities, measure

Qualifications

• 5+ years as a Machine Learning Engineer, Data Scientist, or Applied Scientist.
• 3+ years as an Engineering Manager leading 5+ engineers.
• Hands-on depth in abuse/fraud detection, content classification, behavioral modeling, graph-based modeling, or LLM-based classification.
• Strong communication and cross-functional work ability.

Responsibilities

• Build and lead an exceptional ML engineering team through hiring, coaching, and ownership.
• Drive technical vision and roadmap for Safety ML with partners across Trust & Safety, Product, Policy, Legal, and Data Science.
• Own end-to-end lifecycle of production safety models, from capability definition to performance measurement and operational health.
• Elevate team performance through processes and technical leadership.
• Partner with Trust & Safety on label quality, golden sets, and automating investigations.
• Collaborate with other Engineering Managers to improve the Engineering organization.

Skills

ML engineering

Engineering management

Cross‑functional collaboration

Production ML systems

Job description

Discord is seeking a hands‑on Engineering Manager for the Safety ML team in the US. You will own detection systems for content understanding, account integrity, and platform abuse at scale, guiding both real‑time and batch models.

You will hire, coach, and empower a high‑performing ML engineering group while coordinating with Trust & Safety, Product, Policy, Legal, and Data Science peers. You will drive the end‑to‑end lifecycle of production safety models, define new capabilities, measure