Distinguished Engineer, Machine Learning Systems – Economy

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 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.

At Roblox
, we’re building the tools and platform that empower a global community of creators and developers to build immersive experiences and a dynamic virtual economy. Our Economy ML team sits at the heart of this mission, delivering scalable machine learning systems that power personalization, pricing, search, and content understanding across all Economy surfaces:
Marketplace, Developer Monetization, Payments, and Avatar.

We’re looking for a Distinguished Engineer/Technical Director to lead the strategy and technical direction for ML systems
, with a focus on large‑scale recommendations, infrastructure, and emerging Generative AI applications. You’ll help build the systems that support retrieval, ranking, generative modeling, and LLM‑powered personalization, all at massive scale. This role requires deep systems thinking, hands‑on ML expertise, and a vision for how traditional ML and GenAI come together to power the future of the Roblox economy.

• AI/ML is a top company priority
  , with long‑term investment.
• Real‑world scale
  :
  Power millions of daily economic interactions across ranking, pricing, fraud, and search.
• Full‑system ownership
  :
  Build and optimize end‑to‑end ML pipelines; from data ingestion to GPU training to live inference.
• Complex surfaces, rich signals
  :
  Design systems for 3D content, UGC, avatar metadata, behavioral and economic signals, not just text or images.
• Impact meets innovation
  :
  Shape the future of the Roblox economy while working on frontier ML infra and GenAI workflows.

• Set the technical direction for ML systems powering core economy experiences: personalization, ranking, generative modeling, and more.
• Build and evolve infrastructure for training, serving, and evaluating both traditional ML models and Generative AI models (e.g., embedding‑based retrieval, transformers, LLM‑based workflows).
• Partner with GenAI teams to explore multi‑modal embeddings, avatar generation, and retrieval‑augmented generation (RAG) in economic surfaces.
• Lead efforts to optimize ML system performance: low‑latency serving, efficient GPU training, and cost‑aware inference strategies.
• Guide the development of robust ML pipelines, online feature stores, and experimentation platforms that support both predictive and generative use cases.
• Collaborate with EMs, tech leads, and product partners to align technical architecture with business priorities.
• Mentor senior engineers and help establish a strong technical culture across the Economy ML team.
• Ensure robustness, observability, and scalability of ML systems that power millions of daily economic interactions.
• Own the architecture behind some of Roblox’s most foundational ML systems.
• Work across groups at Roblox to advance the state of ML/AI at the company.
• Help scale a fast‑growing ML organization and define Roblox’s future economy intelligence stack.
• Solve real‑world problems with real user impact, powering millions of personalized, intelligent economic interactions every day.

• 10+ years of experience in software engineering or ML infrastructure, with a strong focus on large‑scale ML systems.
• Deep expertise in building recommendation systems, ranking infrastructure, or real‑time personalization engines.
• Hands‑on experience with Generative AI, such as transformer‑based models, LLMs, embeddings, or RAG pipelines.
• Proven experience with distributed training, model…