Senior Machine Learning Engineer, 3D Data

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 were 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. Were 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 youll 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.

As a Machine Learning Engineer on the Foundation AI organization you will sit at the epicenter of our foundation model efforts. While the research world is focused on architecture you will be the architect of the data flywheel that makes 3DGen possible. You arent just building pipelines; you are building the infrastructure that defines how our models perceive and generate virtual worlds in three dimensions and across time.

In this role you will partner directly with our AI researchers to advance beyond experimental datasets and into the realm of dynamic high-fidelity 3D data synthesis and evaluation. You will bridge the gap between research prototypes working locally to scaling for millions of users. You will design implement and scale robust high-performance infrastructure to crawl create curate store and serve the massive 3D datasets required for these models. We are seeking accomplished software engineers with a passion for data experience building large distributed systems and a commitment to writing high-quality well-tested code to solve complex data challenges at scale. Your contributions will ensure that our foundation models receive the highest quality data thereby supporting the next generation of creative AI.

1. High-Scale Data Orchestration: Architect and maintain automated pipelines for the ingestion cleaning and pre-processing of 3D datasets spanning petabytes of data
2. Synthetic Data Generation: Research and implement synthetic data creation pipelines.
3. Research-to-Production Bridge: Collaborate closely with ML Engineers and Data Scientists to understand their data requirements build tooling that streamlines their data workflows and troubleshoot data-related system issues
4. Scalable Evaluation Frameworks: Build and own evaluationautomating both heuristic-based metrics and human-in-the-loop interfaces to evaluate and benchmark training datasets and in-house foundation models
5. Model Deployment & API Architecture: Design and optimize high-throughput low-latency Inference APIs for internal and external consumer access
6. Autonomous SOTA Tracking: Actively participate in literature reviews and paper reading groups to identify and implement the latest optimizations in generative modeling
7. Resource Efficiency & Observability: Implement monitoring pipeline health optimizing data loading to ensure GPUs are used efficiently

• 5 years of experience as a research-focused data systems engineer (preferably working with 3D generative models)
• Expertise in building scalable ML data pipelines for both batch and real-time environments. Experience working with and processing very large datasets (Petabytes or more)
• Versatile: Youre a generalist and you are comfortable with several languages and technologies already; you are adaptable in any situation
• Team-Player & Technical Leader: You are a collaborative team member who actively mentors peers drives technical excellence and takes ownership of leading and delivering key features and projects across team boundaries
• Python Proficiency: You can write high-quality Python code for automation tooling and infrastructure management
• Are passionate about the potential of generative AI particularly in creative domains like 3D/4D content.
• A Bachelors degree or equivalent experience in Computer Science Computer Engineering or a similar technical field

• MLOps & Data Versioning Expertise: Experience with experiment tracking platforms (e.g. Weights & Biases MLflow) and managing versioning for massive-scale datasets.
• Custom Tooling & Annotation Infrastructure: Proven track record of developing internal human-in-the-loop workflows and annotation tooling tailored to 3D or video data.
• Low-Level Optimization (C): Strong C proficiency to optimize data-loader performance and extend underlying core engine functionality.
• Game Engines & DCC Tools: Hands-on experience developing in Roblox Studio or working with digital content creation tools such as Blender Unreal Engine or Unity.