Principal Machine Learning Engineer (Alt Defense)

Join Roblox as a Principal Machine Learning Engineer in the Alt Defense pod, where you'll lead the technical vision for alternate account detection and prevention. You'll architect high-scale ML systems, solve complex challenges, and drive the ML roadmap. With over 10 years of industry experience in applied ML, expertise in graph learning, and a passion for user safety, you'll make a significant impact on the platform's integrity.

10+ years of industry experience in Applied ML, with a significant focus on anti-abuse, fraud, integrity, or identity

USD 328,610 - 399,420

About Roblox

• Resourceful: You're adaptable in any situation and can always find a path forward in the face of evolving threats
• Team Oriented: You are a sought-after mentor who lifts up your peers and builds a collaborative, high-performance environment
• User Oriented: You understand that safety measures must be balanced with a seamless experience for our legitimate community members
• Mission Oriented: You are laser-focused on keeping Roblox safe and are willing to take bold, strategic risks to achieve a billion-user scale safely

Responsibilities

• Lead the technical vision for the alternate account detection platform, moving from reactive measures to proactive, near real-time prevention.
• Architect high-scale machine learning systems using Graph Neural Networks (GNNs) and advanced clustering techniques to map relationships across billions of entities.
• Drive the machine learning roadmap, identifying opportunities to leverage big data and behavioral signals to improve precision and recall in a high-stakes environment.
• Adversarial mindset: You can think like a bad actor to anticipate how they will circumvent detection and build robust defenses against it

Requirements

• MS or PhD degree in Computer Science, Machine Learning, or a related field
• Experience with high-throughput systems: You understand the nuances of deploying ML models in low-latency environments where "time-to-detect" is a critical KPI
• Expertise in Graph Learning: Deep experience with Large-scale GNNs (GraphSAGE, PGB, etc.) and unsupervised/semi-supervised clustering at the scale of billions of nodes
• Proven track record of leading complex technical projects from conception to production-level deployment
• Analytical: Excited to investigate large, ambiguous datasets to find the "signal in the noise" of billions of accounts