Principal Software Engineer - Economy ML (Data Systems)

Roblox
San Mateo, CA, United StatesPosted 24 February 2026

Job Description

<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><p><strong>Who We Are:</strong></p> <p><strong>Shape the future of Roblox’s virtual economy.</strong></p> <p>The <strong>Economy ML</strong> team is building the machine learning backbone that powers Roblox’s Marketplace, Developer Monetization, and Payments ecosystems. From intelligent pricing and personalized storefronts to dynamic layout optimization and avatar understanding, we’re reimagining how the Roblox economy drives user engagement, monetization, and creator success at scale.</p> <p>As a <strong>Principal Software Engineer (Data Systems)</strong>, you will architect, build and deploy high-scale, reliable real-time and batch data systems for personalization, search and recommendation across various product surfaces in Marketplace, Developer Monetization and Payments. You will be involved in key data projects from architecting event taxonomies and logging interfaces to real-time feature serving across multiple search and recommendation surfaces.</p> <h3><strong>What You’ll Do</strong></h3> <ul> <li>Act as data engineering lead for Economy ML, setting standards for batch vs streaming feature pipelines, table design, observability, and documentation used across the Economy group.</li> <li>Work as a hands-on contributor on our data systems to power content recommendation, search and personalization across Economy product surfaces.</li> <li>Partner with Product, Data Science and ML engineering counterparts to prioritize data initiatives that unlock top-line business goals and reduce tech debt in existing datasets and pipelines.</li> <li>Mentor other DE/ML engineers on best practices for schema design, client logging, experimentation data, and feature pipelines, raising the overall bar for data work.</li> <li>Collaborate with partner and platform teams across Roblox to make sure we are building products with a community first approach.</li> <li>Research and leverage industry-leading practices while making product impact.</li> </ul> <h3><strong>You Have</strong></h3> <ul> <li>8+ years of experience as a product-focused data systems engineer (preferably working with search, recommendation, advertising or personalization systems).</li> <li>Experience designing efficient logging schemas and optimizing data processing pipelines.</li> <li>Experience with real-time stream processing and batch processing (using technologies such as Flink, Spark, Kafka, Druid)</li> <li>Familiarity with feature stores and other machine learning infrastructure.</li> </ul> <p> </p> <h3><strong>You Are</strong></h3> <ul> <li><strong>A Technical Leader</strong>: You have initiated and facilitated challenging technical solutions. Your technical expertise influences product direction. You nurture a culture of technical excellence.</li> <li><strong>Versatile</strong>: You're a generalist and you are comfortable with several languages and technologies already; you are adaptable in any situation. You are resourceful, and take a creative and strategic approach to solving h ... (truncated, view full listing at source)
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