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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Machine Learning Engineer, Embodied AI and Smart NPCs - **Company:** Roblox - **Location:** San Mateo, CA, United States - **Experience:** Experienced - **Salary:** $345,040.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, C Sharp (Programming Language), C++ (Programming Language), Software Quality, Computer Graphics, Game Engine, Python (Programming Language), Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Deep Learning, Backend, Information Technology, Roblox, Feature Extraction - **Published:** September 28, 2026 - **Apply:** https://www.themuse.com/jobs/roblox/principal-machine-learning-engineer-embodied-ai-and-smart-npcs ## About the Role * PhD or Master's in Computer Science, Applied Math, or other field. A record of top-tier publications (e.g., NeurIPS, ICML, CVPR, AAAI, SIGGRAPH, etc) in embodied agents or related domains is a plus. * 7+ years of experience as a Machine Learning Engineer or Research Scientist, applying research to tangible products. * Deep technical understanding of Imitation Learning, Robotics, Reinforcement Learning, Computer Graphics and Vision, with experience working on low-latency motor control (human-like movement) and high-level strategic reasoning (game rules/goals). * Experience with building large scale data/feature pipeline, simulation environments for evaluation / RL. * Experience training models on large-scale distributed clusters and understanding the challenges of inference in real-time gaming environments. * Proficiency in Python (PyTorch/TensorFlow) and familiarity with C#, C++, or similar systems languages. * A passion for bridging the gap between research and production, moving beyond academic benchmarks to launch scalable solutions that directly impact millions of users. ## Description As a Principal Machine Learning Engineer within the Creator Services Machine Intelligence team, you will focus on the research and development of Embodied AI and Behavioral Agents that revolutionize how games are created and played on Roblox. You will bridge the gap between cutting-edge research and massive-scale product application, building agents capable of complex 3D gameplay and unblocking many use cases across Roblox, from automated playtesting to ensure quality, to "ML Players" with human-like movement and strategic reasoning, playing with real players in games. You will work on feature extraction, model training, building validation / RL platform as well as inference set up leveraging methods from imitation learning to reinforcement learning. And you will create generalizable agents that can perceive 3D environments, understand game rules, plan long-term strategies, and execute complex physics-based actions in real-time. You Will: * Design and implement foundation models end to end through the feature extraction to inference for embodied agents. * Define the long-term roadmap for Game AI and Embodied Intelligence, acting as a technical bar-raiser for code quality and architectural design. * Balance the exploration of cutting-edge deep learning research with the practical constraints of serving models to millions of concurrent users. * Mentor fellow engineers and researchers, fostering a culture of technical excellence and scientific inquiry. * Collaborate with Product Managers, Backend and Game Engine Engineers and other Roblox team members. ## Related Videos - [Robots 2.0: When artificial intelligence meets steel](https://www.wearedevelopers.com/videos/1452-robots-2-0-when-artificial-intelligence-meets-steel) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [How Robots Learn to be Robots](https://www.wearedevelopers.com/videos/1632-how-robots-learn-to-be-robots) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [John Romero - What AI Can, Can’t, and Shouldn’t do for Games](https://www.wearedevelopers.com/magazine/478-john-romero-what-ai-can-can-t-and-shouldn-t-do-for-games) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)