Principal Machine Learning Engineer, Alt Defense

Overview

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences—all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and we’re looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

Safety and Civility is Roblox’s #1 priority. The Alt Defense pod focuses on Alternate Account Detection and Prevention. Our goal is to stop bad actors who try to return with new identities. As the Technical Lead for this pod, you will architect and build an industry-leading detection system that operates at a massive scale—processing billions of accounts and identifying recidivism within minutes.

You will support additional use cases for alt detection across the company and report to the Senior Engineering Manager of the Account Identity Team.

• Lead the technical vision for the alternate account detection platform, moving from reactive measures to proactive, near real-time prevention.
• Architect high-scale ML systems using Graph Neural Networks (GNNs) and advanced clustering techniques to map relationships across billions of entities.
• Solve complex ground truth and training data challenges for adversarial use cases.
• Build for latency and scale, ensuring that detection happens within minutes of a bad actor’s rejoin attempt.
• Develop innovative adversarial approaches to stay ahead of sophisticated actors who use evolving techniques to mask their identity.
• Drive the ML roadmap, leveraging big data and behavioral signals to improve precision and recall in a high-stakes environment.
• Mentor and up-level a pod of high-performing ML and software engineers, fostering a culture of technical excellence and rapid iteration.

• MS or PhD in Computer Science, Machine Learning, or a related field.
• 10+ years of industry experience in Applied ML, with a focus on anti-abuse, fraud, integrity, or identity.
• Expertise in Graph Learning:
  Large-scale GNNs (Graph
  
  SAGE, 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 deployment.
• Experience with high-throughput systems: deploying ML models in low-latency environments where time-to-detect is a key KPI.
• Adversarial mindset: ability to think like a bad actor to anticipate and defend against evasion tactics.

• Resourceful: adaptable in evolving threat scenarios.
• Analytical: able to investigate large, ambiguous datasets to find meaningful signals.
• User-oriented: balance safety with a seamless experience for legitimate users.
• Team-oriented: a mentor and collaborator who lifts peers and fosters high performance.
• Mission-oriented: focused on keeping Roblox safe and scalable to a billion users.

For roles based at our headquarters in San Mateo, CA, the starting base pay is the range shown below. The actual base pay depends on factors such as background, experience, location, and market demand. The salary may fall outside this range in some circumstances. This pay range may change and is eligible for equity and benefits as described on this page.

Annual Salary Range

$295,250 — $345,040 USD

Roles based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Roblox provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type. We provide reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.