Engineering Manager, Machine Learning (Safety)

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games.

Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games.

Discord's Safety ML team builds the machine learning systems that protect 200M+ users.

The team's mission is to make Discord a place where people can build genuine friendships without exposure to harm, at a scale where manual review alone can never keep up.

We're looking for a highly technical, hands-on, and mission-driven Engineering Manager to lead our Safety ML team.

As the manager responsible for Safety ML, you will own the detection systems that sit between attackers and our users; real-time and batch models for content understanding, account integrity, and platform abuse.

• Build and lead an exceptional team of highly-engaged ML engineers by hiring, coaching, and instilling a sense of ownership and impact.
• Drive the technical vision and roadmap for Safety ML by collaborating with your team and partners across Trust & Safety, Product, Policy, Legal, and Data Science.
• Own the end-to-end lifecycle of production safety models: defining new capabilities, measuring performance, and monitoring the operational health of systems that make millions of enforcement decisions per day.
• Manage processes and leverage your technical expertise to continually raise the bar and ensure your team delivers extraordinary results.
• Partner with Trust & Safety on label quality, golden sets, and automating manual investigations.
• Work with other Engineering Managers to continuously improve the Engineering organization and uphold our workplace philosophy.

What you should have

• You have 5+ years of experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist.
• You have 3+ years of experience as an Engineering Manager and successfully managed a team of 5+ engineers.
• You have hands-on depth in at least one of: abuse/fraud detection, content classification, behavioral modeling, graph-based modeling, or LLM-based classification systems.