Senior Machine Learning Engineer, AI Platform - PhD Early Career

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.

The Foundation AI Group is on a mission to establish Roblox as the standard for 3D foundational models (3

DFMs), democratizing creation by making it simple for anyone to generate high-quality, immersive 3D experiences using AI. The AI Platform team is a foundational part of this vision, supporting hundreds of ML use cases and billions of inferences daily across Discovery, Safety, Engine, and more. We are seeking exceptional PhD new graduates to drive innovation across three critical areas:
AI Platform, Distributed Inference Systems, and Generative AI Information Retrieval.

As a Senior Machine Learning Engineer on the AI Platform team, you will be a key contributor to building the cutting‑edge systems that power AI  will focus on one of three high‑impact tracks:

• 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.

• Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.
• Conduct deep, low‑level performance analysis and optimise ML models (using techniques like continuous batching, speculative decoding, and quantisation) and systems on GPU architectures to maintain peak performance and stability.

• Lead the design and development of Retrieval‑Augmented Generation (RAG) systems.
• Build and maintain core information retrieval infrastructure—vector databases and knowledge graphs—to enable accurate grounding of Gen AI models.
• Ship language models and 3D objects as a service for the Roblox community, making creation easier.

• 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.
• LLMs—Fine tuning, Safety.
• Agentic systems—Agent evaluation, context engineering.
• Experience building agentic applications with context for real‑world applications.
• Collaborative mindset and experience integrating and deploying optimised 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

You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.

As you apply, you can find more information about our process by signing up for Speak_. You’ll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you…