Principal Machine Learning Engineer, Content Safety

<div class="content-intro"><p><span style="font-weight: 400;">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. </span></p> <p><span style="font-weight: 400;">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.</span><strong> </strong><span style="font-weight: 400;">We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. </span></p> <p><span style="font-weight: 400;">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.</span></p></div><h2><strong>Why Content Safety?</strong></h2> <p>As a<strong> Principal Machine Learning Engineer</strong> for Content Safety, you will define the future of proactive moderation, driving immense social impact through cutting-edge, innovative ML solutions, focused on critical and ambiguous safety challenges.</p> <p>You will set the <strong>3-5 year technical strategy and architectural blueprint</strong> for how Roblox uses machine learning for content moderation. <strong>You will own the architectural and execution roadmap </strong>of massive-scale ML systems that mitigate violative UGC content before it impacts our community.</p> <p>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 our broad community of over 100 million daily active users.</p> <h2><strong>You will:</strong></h2> <ul> <li><strong>Define and Own the Technical Vision:</strong> Define and lead the <strong>multi-year technical vision, architectural strategy, and execution</strong> for machine learning solutions in Content Safety, ensuring these systems proactively and effectively detect and mitigate violative content at massive scale.</li> <li><strong>Strategic Stakeholder Partnership:</strong> 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.</li> <li><strong>Lead Innovation:</strong> Oversee the adoption and safe deployment of innovative machine learning techniques (e.g., transfer-learning, self-supervised learning, quantization, LoRA, distillation).</li> <li><strong>Drive End-to-End Product Development:</strong> You will not just model; you will build. You will work cross-functionally to construct datasets from scratch where none exist, build auto-labeling pipelines, and ship solutions to solve novel technical problems.</li> <li><strong>Ship Code, Not Just Models:</strong> Expect to spend roughly <strong>30-40% of your time on backend and integration work</strong>. You will be responsible for integrating your work into the production stack, leveraging modern AI coding tools (e.g., Cursor) to accelerate velocity and handle infrastructure complexity</li> </ul> <h2><strong>You have:</strong></h2> <ul> <li><strong>8+ years</strong> of experience designing, developing, and operating large-scale, high-impact machine learning systems in a production environment.</li> <li>A proven track record of successfully setting the <strong>long-term technical direction</strong> for an entire ML domain, demonstrating the ability to take ambiguous problems from concept to scaled production impact.</li> <li>Deep expertise in advanced ML architectures and techniques, including<strong> Computer Vision (CV) ... (truncated, view full listing at source)