[2026] Senior Machine Learning Engineer (Systems), Embodied AI/NPCs, ML Platform - PhD Early Career

Team Creator Services Machine Intelligence Team

The Machine Intelligence team is building an NPC system that can (1) play any Roblox game and (2) perform real-time inference efficiently enough to support deployment to all Roblox players.

ML Platform Team

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

What You Will Do

As a Senior Machine Learning Engineer, you will be a key contributor to building the cutting-edge systems that power AI at Roblox.

Creator Services Machine Intelligence Team Responsibilities

• Develop Scale Data Pipelines: Design, build and maintain robust data pipelines to collect complex 3D game states and real-time player actions across the platform.
• Train Novel Architectures: Solve the feature extraction across games for NPC model in a general and scalable way and drive model training speed for novel, sophisticated deep learning architectures.
• Optimize Real-Time Inference: Engineer high-performance model inference solutions to support the seamless deployment of 10s to 100s of autonomous NPCs in real-time environments.

ML Platform Team Track 1: AI Platform Projects

• Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of
• 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.

ML Platform Team Track 2: Distributed Inference & Systems Optimization

• Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.
• Optimize our inference engine to serve millions of QPS at low latency.
• Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.

You Have

• 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.
• Built end-to-end ML pipelines and managed model inference and deployment.
• Experience with novel datasets, and building real-world agentic applications.
• Scaled high-performance, high-availability architectures.
• Handled infrastructure using Kubernetes and major cloud providers (AWS, Azure, or GCP).

Salary

For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, locatio