Distinguished Engineer, Machine Learning Systems – Economy

Overview

Lead the strategy and technical direction for machine learning systems powering the Roblox economy, with a focus on large-scale recommendations, infrastructure, and Generative AI applications.

What you'll do

• 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

What you'll need

• 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 deployment, and GPU-accelerated workflows
• Strong understanding of ML system architecture: data pipelines, feature stores, inference optimization, experimentation tooling
• Systems-first mindset with strong instincts around scale, cost, performance, and reliability
• Track record of leading large technical initiatives and mentoring senior engineers
• BS, MS, or PhD in Computer Science, Machine Learning, or a related field

Details

• Location: San Mateo, CA, United States (headquarters)
• Onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday
• Annual base salary range: $397,460 to $455,720 USD
• Full-time employees are also eligible for equity compensation and benefits
• For US based roles only: the Company may not be able to employ candidates who have US work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time