Schemata is a spatial intelligence company that is building the world's AI interface. Immersive, AI-native training built for the speed and scale of modern operations. Backed by a16z speedrun.
About the role
Research, prototype, and fine-tune state‑of‑the‑art methods for 3D reconstruction, segmentation, and feature embedding (e.g., 3DGS, DINO, RoPE, FlowR models). Design data pipelines that convert heterogeneous inputs (CAD, LiDAR, mesh, simulation output) into unified, queryable scene‑graphs.
What they're looking for
- PhD with 3DGS-related work or 4+ years industry experience in 3D computer vision, robotics, graphics, segmentation, or VLM/MLLM model training and application
- Strong programming skills and understanding of applied deep‑learning frameworks and model architectures
- Hands‑on experience with 3D data types: point clouds, meshes, 3DGS representations
- Solid grounding in linear algebra, geometry and numerical optimization
- Demonstrated ability to convert research into reliable, maintainable production code and services
- Experience profiling GPU workloads and scaling distributed training or real‑time inference pipelines
More about this role
At Schemata, we are transforming the $400 B virtual‑training and simulation market by fusing 3D computer vision, neural rendering and large multimodal models inside highly regulated industries. Our platform delivers photorealistic, intelligent 3D experiences, demanding robust spatial reasoning, high‑performance data pipelines and seamless integration between traditional graphics and AI‑driven perception.
About the Role
We are seeking a highly-specialized Spatial Computing Engineer to join our team full‑time. You will play a foundational role in designing, building and optimizing the 3D and spatial intelligence pipelines that turn raw capture data into actionable world models for next‑generation simulation and training applications.
This is a high‑impact, cross‑functional role: you will work end‑to‑end from cutting‑edge research prototypes to production inference and performance profiling, ensuring our applications understand complex environments and respond in real time across diverse deployment targets.
Research, prototype, and fine-tune state‑of‑the‑art methods for 3D reconstruction, segmentation, and feature embedding (e.g., 3DGS, DINO, RoPE, FlowR models).
Design data...
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