Principal Machine Learning Engineer, Account Authentication

Why Account Authentication?

Safety and Civility is Roblox's #1 priority and our mission is to protect our community. As a Principal Machine Learning Engineer on the Account Authentication and Security team, you’ll be driving our classification and anomaly detection efforts to identify and mitigate account takeovers using a wide variety of signals. This is particularly challenging because the Roblox community is incredibly varied and their interactions with the platform are deep. In addition to millions of players, many of our users  are creators, some even parents.  Creativity is crucial. Our current efforts are nascent. 

Responsibilities:

• Drive the design, development, and deployment of our ML models for account security, including account takeover detection and anomaly detection in authentication flows.
• Identify, propose, and lead new ML initiatives that enhance both account security and the onboarding experience.
• Oversee ML project lifecycles end-to-end, from scoping and data collection to modeling, evaluation, productionization, and ongoing monitoring.
• Define and enforce standards for ML model quality, reliability, and operational excellence.
• Provide technical leadership and mentorship to ML engineers and set best practices for the broader Accounts organization.
• Collaborate cross-functionally with product managers, data scientists, engineers, and UX teams to align technical solutions with business priorities.
• Influence the long-term technical direction and roadmap for ML in account security across Roblox.

Requirements:

• Demonstrated expertise building, deploying, and maintaining ML models for classification, anomaly detection, or fraud prevention at large scale.
• Experience leading high-impact ML projects and setting technical direction at an organizational level.
• Deep skills in data modeling, feature engineering, ML architecture, and evaluation.
• Proven ability to mentor engineers, lead technical discussions, and drive adoption of ML best practices across teams.
• Fluency in Python and major ML/data science libraries.
• Experience collaborating with stakeholders outside engineering to clarify goals and drive alignment.
• Bonus: Experience with account security and authentication, or detection of spam/abuse/growth risk.
• Bonus: Familiarity with GoLang, Rust, C#, or Lua.
• Bonus: Background in Datascience.