---
title: 'Research Scientist - 3D Diffusion at SpAItial'
canonical: 'https://feeny.ai/job/research-scientist-3d-diffusion-spaitial-london-f21y5vjxxmzm'
type: 'job'
last_seen: '2026-09-06'
---

# Research Scientist - 3D Diffusion at SpAItial

- **Company:** SpAItial
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-03-29
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/spaitial/b0ab6083-efbb-43df-b192-3746a51293b1

## Job description

SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality. We are moving beyond 2D pixels to build models that natively understand the physics and geometry of our world. Our mission is to redefine how industries, from robotics and AR/VR to gaming and cinema, generate and interact with physically-grounded 3D environments.

We're looking for bold, innovative individuals driven by a passion for pushing the boundaries of generative 3D AI. You should thrive in an environment where creativity meets technical challenge and be fearless in tackling the hardest problems in 3D world modeling. Our team is built on a foundation of dedication and a shared commitment to excellence, so we value people who take immense pride in their work and place the collective goals of the team above personal ambition. As a part of SpAItial, you'll be at the forefront of building World Models that bridge generative AI and the physical world. If you're ready to make an impact, embrace the unknown, and collaborate with a talented group of visionaries, we want to hear from you.

We're seeking a Research Scientist focused on 3D diffusion. You will lead research to design, build, train, evaluate, and optimize diffusion-based generative models that produce high-quality 3D content from images, video, and other inputs, with an emphasis on world-scale scenes that are spatially consistent and physically grounded.

## Responsibilities

- Design and develop diffusion-based methods for 3D generation from images, video, and other inputs.
- Build, train, optimize, and evaluate 3D diffusion models, including research on architectures, losses, and sampling strategies.
- Apply and adapt cutting-edge image and video diffusion backbones (e.g., Stable Diffusion, FLUX, WAN, or comparable systems) to 3D generation.
- Implement and experiment with state-of-the-art 3D representations including point clouds, meshes, and 3D Gaussian Splatting.
- Develop training pipelines and loss functions that improve geometry accuracy, visual fidelity, and spatiotemporal consistency.
- Collaborate with researchers to integrate physics-aware priors and world model capabilities into diffusion systems.
- Analyze model performance, debug failure cases, and iterate rapidly to improve quality and robustness.

Key Qualifications:

- PhD in computer science, computer vision, graphics, machine learning, or a related field.
- Top-tier publication record at venues such as CVPR, ECCV/ICCV, NeurIPS, and SIGGRAPH.
- Strong fundamentals in deep learning and generative modeling, in particular diffusion models and large transformer models.
- Hands-on experience training diffusion models and working with cutting-edge image and video model stacks (e.g., Stable Diffusion, FLUX, WAN, or similar).
- Solid understanding of 3D processing concepts such as camera geometry, depth, reconstruction, point clouds, meshes, or Gaussian splats.
- Proficiency in Python and deep learning frameworks such as PyTorch, with experience in large-scale model training and optimization.
- Ability to implement research ideas, run rigorous experiments, and ship reliable ML code.

At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.

## About SpAItial

## Company Overview
- **One-liner**: SpAItial builds physically-grounded world models — AI that generates and reasons about the appearance and physics of real and imagined 3D environments.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: London, United Kingdom (also has offices in Germany, United States, Luxembourg)
- **Founded**: 2024 (LinkedIn) / 2025-01-01 (company schema) — likely incorporated in late 2024, publicly launched May 2025
- **Founders**: Matthias Niessner (CEO), Luke Rogers (COO), Ricardo Martin‑Brualla, David Novotný

## Core Business
- **Primary industry/industries**: Spatial AI, 3D generative AI, foundation models, computer graphics
- **Target customers**: Developers, game studios, film/VFX, VR/AR platforms, robotics companies, industrial simulation (B2B); also provides a consumer app for world generation (B2C)
- **Mission or purpose**: “Bridging the virtual and physical – building physics‑consistent, spatio‑temporally grounded AI that understands the 3D world like humans do.”

## Products & Services
- **[Echo (Model Family)](https://spaitial.ai/)**: A series of Spatial Foundation Models (Echo‑1, Echo‑2, Echo HQ) that generate persistent 3D Gaussian Splat worlds from a single image, text prompt, or 360° panorama. Outputs are real‑time explorable and physically plausible.
- **[SpAItial API](https://spaitial.ai/)**: Programmatic access to Echo for agents, tools, simulations, and creative pipelines. Supports async generation, webhooks, and multiple output formats (SPZ, SOG, PLY, collision meshes).
- **[SpAItial App](https://spaitial.ai/)**: A web and desktop application for creating, editing, and sharing worlds generated by Echo. Includes image‑to‑world, text‑to‑world, sculpting, painting, and export tools.
- **Startup Program**: Credits, priority API access, early model access, and direct feedback loops for startups building with spatial AI.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: **Total Funding** — USD 13,000,000 (Seed round, closed June 27, 2025)
- **Notable Investors/Partners**:
  - Lead: Earlybird Venture Capital
  - Participants: Speedinvest
  - Notable angels: Robin Rombach (Black Forest Labs), Victor Riparbelli & Steffen Tjerrild (Synthesia), Christian Stiebner, Edward Grefenstette, Jon Barron, Rahul Garg, Sergej Epp (Sysdig/Palo Alto), Elias Schneider (Codesphere), Paul Whitehead (Zoopla), and others.
- **Growth Signals**:
  - Headcount: 20 employees (+2000% YoY from 1 employee the year prior)
  - Active job postings: 11 (monthly growth +22.2%, quarterly +175%)
  - Strong hiring across research, engineering, and ML infrastructure
  - Launched Echo‑2 in May 2026, Echo HQ in June 2026
  - Opened early access and startup program

## Competitive Advantages
- **Spatial Foundation Models (SFMs)**: Unlike LLMs, image, or video models, SFMs operate natively in 3D physical space, capturing geometry, materiality, and physics — enabling true spatial reasoning and physically consistent generation.
- **World‑class founding team**: Deep expertise from academia (TU Munich), big tech (Google, Meta), and scaled startups (Synthesia, Cazoo). Includes pioneers in generative 3D (GRAF, VoxGRAF, X‑Fields).
- **Real‑time, persistent 3D worlds**: Outputs are not just images or videos but fully explorable Gaussian Splat environments that can be edited, exported, and shared.
- **Strong investor backing**: $13M seed from top European VCs and influential angel investors validates the technology and vision.

## Strategic Focus
- **Model scaling**: Improving core model capabilities (Echo‑2, Echo HQ) for richer geometry, sharper detail, and stability.
- **Developer ecosystem**: Building out the API, documentation, and startup program to attract developers and partners.
- **Industry partnerships**: Piloting technology across gaming, film, CAD, VR/AR, and robotics — collaborating with leading organizations.
- **Talent acquisition**: Growing the team aggressively across research, engineering, and infrastructure.

## Why Work Here
- **Cutting‑edge research**: Work on frontier AI problems at the intersection of computer vision, graphics, and 3D generative models. Publishable research encouraged.
- **Strong team**: Colleagues from Meta, Google, TU Munich, Synthesia, and top labs. Low ego, high output.
- **Early stage impact**: Join at 20 people — your work directly shapes the product, culture, and direction of the company.
- **Global, hybrid‑friendly**: Headquarters in London with presence in Munich (Germany), New York (US), and Luxembourg. Mix of in‑person and remote collaboration.
- **Open roles** (as of mid‑2026): Research Scientist (3D Diffusion, World Models), Research Engineer (Graphics, World Models), ML Infrastructure Engineer — 11 active postings.
- **Perks**: Not publicly detailed, but seed‑stage startup typically offers equity, flexible time off, and direct access to founders.
- **Culture**: Described as “research meets real‑world application” — a blend of academic rigor and product‑focused execution.

## Sources
1. [spaitial.ai](https://spaitial.ai/) – Company homepage, product overview, API docs, blog
2. [spaitial.ai/about](https://spaitial.ai/about) – About page, mission, team, funding announcement
3. [spaitial.ai/careers](https://spaitial.ai/careers) – Careers page, open roles
4. [spaitial.ai/blog/announcing-spaitial](https://spaitial.ai/blog/announcing-spaitial) – Launch blog post with detailed team, funding, and vision
5. [LinkedIn – SpAItial AI](https://uk.linkedin.com/company/spaitial-ai) – Employee count, funding, headcount growth, open roles, talent sources

## Other roles at SpAItial

- [Technical Artist](https://feeny.ai/job/technical-artist-spaitial-london-kdgkjp9c2nx6) — London, United Kingdom
- [Business Operations Manager](https://feeny.ai/job/business-operations-manager-spaitial-london-fwsemcnhjvws) — London, United Kingdom
- [Research Scientist - Robot Learning (VLA / WAM)](https://feeny.ai/job/research-scientist-robot-learning-vla-wam-spaitial-london-97ghdtvn8cmv) — London, United Kingdom
- [Research Scientist - 3D Reconstruction (SfM & SLAM)](https://feeny.ai/job/research-scientist-3d-reconstruction-sfm-slam-spaitial-london-dgx907pgrv08) — London, United Kingdom
- [Machine Learning Systems & Infrastructure Engineer](https://feeny.ai/job/machine-learning-systems-infrastructure-engineer-spaitial-london-yg2ny2hqnfkr) — London, United Kingdom
- [Machine Learning & Cloud Infra Engineer](https://feeny.ai/job/machine-learning-cloud-infra-engineer-spaitial-london-p5w3sxeysvq7) — London, United Kingdom
- [Research Engineer - 3D World Models](https://feeny.ai/job/research-engineer-3d-world-models-spaitial-london-68tajf2mpe9t) — London, United Kingdom
- [Research Engineer - Graphics](https://feeny.ai/job/research-engineer-graphics-spaitial-london-scfpn9d65rd2) — London, United Kingdom
- [Research Scientist - World Models](https://feeny.ai/job/research-scientist-world-models-spaitial-london-txvdt70j5zfj) — London, United Kingdom