Spatial Computing Research Engineer

Schemata; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary

Meaningful equity stake

Comprehensive health coverage

401(k) plan

Paid parental leave

High visibility and impact

Job summary

Schemata in San Francisco seeks a highly specialized Spatial Computing Engineer to design and optimize 3D and spatial intelligence pipelines that transform raw capture data into actionable world models for next‑generation simulation and training.

You will work end‑to‑end from research prototypes to production inference, collaborating with graphics and product engineers to ship features blending neural perception with real‑time rendering.

Qualifications

• PhD with 3DGS-related work or 4+ years industry experience in 3D CV, 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.

Responsibilities

• 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.
• Integrate multimodal foundation models (LLMs, VLMs) with spatial representations to power real-time diagnostics, step-by-step instruction and autonomous evaluation in training scenarios.
• Implement GPU-accelerated training/inference, synthetic-data generation, and large-scale evaluation workflows in cloud and edge environments.
• Collaborate with graphics and product engineers to ship mission-critical features that blend neural perception with real-time rendering.
• Publish internally, attend CVPR / NeurIPS / SIGGRAPH, and translate the latest research into production capabilities.

Skills

PhD in 3DGS

Deep learning

3D data types

Linear algebra

Production code

GPU profiling

Education

PhD in 3DGS

BS or MS in related field

Tools

GPU acceleration

Job description

About Schemata

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.

Core Responsibilities

• 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.

• Integrate multimodal foundation models (LLMs, VLMs) with spatial representations to power real‑time diagnostics, step‑by‑step instruction and autonomous evaluation in training scenarios.

• Implement GPU‑accelerated training/inference, synthetic‑data generation, and large‑scale evaluation workflows in cloud and edge environments.

• Collaborate with graphics and product engineers to ship mission‑critical features that blend neural perception with real‑time rendering.

• Publish internally, attend CVPR / NeurIPS / SIGGRAPH, and translate the latest research into production capabilities.

Essential Skills & Experience

• 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.

Nice to Have

• Tier‑1 conference publications (CVPR, NeurIPS, SIGGRAPH) or open‑source contributions in 3D AI.

• Large‑scale data‑engineering / MLOps experience for model training.

• Reinforcement‑learning or embodied‑AI background.

• Defense, aerospace or other regulated‑industry experience; active or ability to obtain U.S. security clearance.

Why Join Us?

• Competitive salary that reflects your experience and track record

• Meaningful equity stake in a high-growth, venture-backed defense tech startup, so you share in the upside you help create

• Comprehensive health coverage: medical, dental, and vision insurance

• 401(k) plan

• Paid parental leave

• High visibility and real impact: Collaborate with world‑class engineers and researchers in a high-ownership environment.