Roblox is a platform where millions of users explore, create, and connect through immersive 3D experiences. The company is seeking a Senior Machine Learning Engineer to contribute to the AI Platform team, focusing on building systems that support a variety of machine learning use cases.

Responsibilities

• Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox
• Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes
• Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable

Skills

• Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox's research areas
• Experience with high performance distributed systems, ML Infrastructure, LLM fine tuning/RL, Information Retrieval and Gen AI context generation
• Expertise in one or more of the following key areas: AI/ML Platform Data stores - Features stores, Vector DBs and Knowledge Graphs
• Expertise in LLMs - Fine tuning, Safety
• Expertise in Agentic systems - Agent evaluation, context engineering
• Experience building agentic applications with context for real world applications
• Collaborative mindset and experience integrating and deploying optimized models with cross-functional teams, including data scientists and software engineers
• Experience with graph databases and large-scale GNNs (Graph Neural Networks)
• Experience working with Kubernetes
• Experience working with one or more cloud providers (e.g., AWS, Azure, GCP)
• Experience working with high availability systems
• Experience working with ML models, LLMs or other AI systems

Benefits

• All full-time employees are also eligible for equity compensation
• Benefits as described on [this page](https://careers.roblox.com/total-rewards)
• Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Company Overview