Engineering Manager, Machine Learning (Safety)

About the role

Discord plays a uniquely important role in the future of gaming. 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.

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 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.

Requirements

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. You have strong communication skills and the ability to work well cross-functionally. You thrive in ambiguous environments and get excited about figuring out solutions to complex problems, and then executing on them. You are a first principles thinker that can work with others to come up with pragmatic solutions. You have a proven record of shipping ML systems to production at scale. You are passionate about coaching and leading other engineers, but can roll up your sleeves and get elbow deep in code when needed. You keep up with the industry trends and continuously identify new technologies to leverage to solve technical problems.

Qualifications

The US base salary range for this full-time position is $272,000 to $306,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.

Skills

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. You have strong communication skills and the ability to work well cross-functionally. You thrive in ambiguous environments and get excited about figuring out solutions to complex problems, and then executing on them. You are a first principles thinker that can work with others to come up with pragmatic solutions. You have a proven record of shipping ML systems to production at scale. You are passionate about coaching and leading other engineers, but can roll up your sleeves and get elbow deep in code when needed. You keep up with the industry trends and continuously identify new technologies to leverage to solve technical problems.

Benefits

Our benefits package includes:

• Health insurance
• Retirement savings plan
• Flexible work schedule
• Professional development opportunities

Pay

The US base salary range for this full-time position is $272,000 to $306,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.

Schedule

We offer a flexible work schedule to accommodate your needs.