
Engineering Manager
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in San Francisco, United States"), this listing's salary midpoint is about 80% higher. The offer sits above the benchmark range (€10,707–€16,060). The listed pay band (€22,667–€25,500) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 3 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Engineering Manager | €8,179/per month | €13,254/per month | €21,167/per month |
| All roles in San Francisco, United States | €10,707/per month | €14,107/per month | €16,060/per month |
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. What You'll Be Doing 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. 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 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. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.
Job Details
Responsibilities
- Build and lead an exceptional team of ML engineers by hiring, coaching, and instilling ownership and impact
- Drive the technical vision and roadmap for Safety ML in collaboration with cross-functional partners
- Own the end-to-end lifecycle of production safety models: defining capabilities, measuring performance, monitoring health
- Manage processes and leverage expertise to raise the bar and deliver results
- Partner with Trust & Safety on label quality, golden sets, and automating investigations
- Collaborate with other Engineering Managers to improve the Engineering organization and workplace philosophy
Requirements
- 5+ years of experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist
- 3+ years of experience as an Engineering Manager supervising a team of 5+ engineers
- Hands-on depth in at least one area: abuse/fraud detection, content classification, behavioral modeling, graph-based modeling, or LLM-based classification
- Strong communication and cross-functional collaboration skills
- Comfort with ambiguity and solving complex problems
- Proven track record of shipping ML systems to production at scale
Skills & Technologies
Education Level
No degree required
| Location | Active listings |
|---|---|
| Remote - Global | 1 |
| Role type | Active listings |
|---|---|
| Engineering Manager | 1 |
| Role level | Active listings |
|---|---|
| Manager | 1 |
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