Engineering Manager, Machine Learning (Safety)

Discord•San Francisco, CA

4d•$272,000 - $306,000

About The Position

Discord's Safety ML team builds the machine learning systems that protect over 200 million 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. This role is for a highly technical, hands-on, and mission-driven Engineering Manager to lead the Safety ML team. The manager will own the detection systems that sit between attackers and users, including real-time and batch models for content understanding, account integrity, and platform abuse.

Requirements

5+ years of experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist.
3+ years of experience as an Engineering Manager and 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 the ability to work well cross-functionally.
Thrive in ambiguous environments and get excited about figuring out solutions to complex problems, and then executing on them.
A first principles thinker that can work with others to come up with pragmatic solutions.
Proven record of shipping ML systems to production at scale.
Passionate about coaching and leading other engineers, but can roll up your sleeves and get elbow deep in code when needed.
Keep up with the industry trends and continuously identify new technologies to leverage to solve technical problems.

Responsibilities

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 the 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 technical expertise to continually raise the bar and ensure the 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 the workplace philosophy.