Principal Machine Learning Engineer, Content & Communication Safety

Roblox • San Mateo, CA

62d

About The Position

At Roblox, we strive to connect a billion people with optimism and civility, and the Safety organization's mission is to become the leader in civil immersive online communities. We systematically and proactively detect, remove, and prevent problematic content and behavior. In doing so, we keep Roblox safe, civil, and inclusive, fostering positive relationships between people around the world. As a Principal Machine Learning Engineer for Safety AI Systems, you will define the future of proactive moderation, driving immense social impact through cutting-edge, innovative ML solutions. This role is a fusion of a Principal Engineer's technical authority and an Engineering Manager's leadership, focused on the most critical and ambiguous safety challenges. You will set the 3-5 year technical strategy and architectural blueprint for how Roblox uses machine learning-from high-velocity text filtering to leveraging multimodal Generative AI-to combat the most complex critical harms on the platform. You will own the execution roadmap and technical planning, directly guiding the launch of high-priority new ML projects. You will be responsible for defining the standards of innovation in data quality, model robustness, and ethical deployment across the entire Content & Communication Safety ML pillar. You will lead and scale a high-performing group of individual contributors, providing both strategic oversight and hands-on guidance to the teams responsible for the architectural development of massive-scale systems that mitigate abuse and harassment before it impacts our community. You will feel a deep sense of responsibility in proactively protecting our community-thoughtfully and fairly-while balancing user freedom with platform civility. Your efforts will ensure Roblox remains one of the safest places on the internet for users.

Requirements

• 8+ years of experience designing, developing, and operating large-scale, high-impact machine learning systems in a production environment.
• 5+ years of experience in technical leadership, management, or mentorship roles, ideally having managed Engineering Managers or Principal/Staff-level individual contributors.
• A proven track record of successfully setting the long-term technical direction for an entire ML domain or pillar, demonstrating the ability to take ambiguous problems from concept to scaled production impact.
• Deep expertise in advanced ML architectures, including Large Language Models (LLMs), transfer learning, or other foundation model technologies, especially applied to text or multimodal data.
• Expertise in architecting scalable, real-time ML inference services and robust data pipelines operating at millions of requests per second.
• Demonstrated success in leading and resolving high-stakes, cross-functional conflicts and technical disagreements, with an ability to build consensus among diverse stakeholders.
• Exceptional product sense and strategic planning ability: able to translate platform safety requirements into an achievable, iterative technical roadmap.

Responsibilities

• Define and Own the Technical Vision: Define and lead the multi-year technical vision, architectural strategy, and execution for machine learning solutions across Content and Communication Safety, ensuring these systems proactively and effectively detect and prevent high-severity, critical harms at massive scale.
• Provide Principal-Level Architecture: Act as the highest technical authority for the Content Safety ML domain, guiding the architecture and long-term maintainability of foundational models, data pipelines, and real-time inference services.
• Drive Cross-Org Alignment: Identify and champion the most ambiguous, high-leverage technical problems, driving alignment and securing investment for organization-wide ML infrastructure and platform development initiatives that benefit all of Trust & Safety.
• Lead Innovation in Safety: Oversee the adoption and safe deployment of innovative technologies (e.g., advanced NLP, self-supervised learning, multimodal LLMs) to anticipate and mitigate novel abuse vectors, moving beyond reactive detection to proactive intervention.
• Strategic Stakeholder Partnership: Collaborate with executive-level Product, Data Science, Policy, and Operations leaders to define and prioritize the strategic machine learning roadmap, influencing product strategy and demonstrating the impact of ML on user trust and safety outcomes.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Industry: Administrative and Support Services
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees