--- title: 'Research Scientist - 3D Reconstruction & Novel View Synthesis at SpAItial' canonical: 'https://feeny.ai/job/research-scientist-3d-reconstruction-novel-view-synthesis-spaitial-london-y27h8v9y25vn' type: 'job' last_seen: '2026-10-18' --- # Research Scientist - 3D Reconstruction & Novel View Synthesis at SpAItial - **Company:** SpAItial - **Location:** London, United Kingdom - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-10-05 - **Last confirmed live:** 2026-10-18 - **Apply:** https://jobs.ashbyhq.com/spaitial/28838287-1364-49a7-b842-920525666f61 ## 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 seeking a Research Scientist to push the state of the art in 3D reconstruction. You should have command of the latest scene representations, such as Gaussian splats and radiance fields, and of reconstruction methods across the full range, from per-scene optimization to feed-forward models. We are looking for someone who knows the field well enough to choose the right representation and method for a problem, and then improve on it. This is a senior, hands-on research role for someone who has already done reconstruction research across more than one representation. ## Responsibilities - Advance the state of the art in 3D reconstruction, from research ideas to working methods. - Work across the full range of reconstruction problems (geometry, appearance, materials, lighting and dynamics, from sparse or incomplete observations), and novel view synthesis, including neural rendering and feed-forward view generators. - Design losses, priors, and optimization strategies that improve fidelity, robustness, and efficiency. - Build rigorous evaluations on public and internal benchmarks, and use them to drive decisions. - Collaborate with research and engineering colleagues to bring successful methods into production systems. ## Key qualifications - PhD in computer vision, graphics, or a related field; publications at top venues (CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS). - Deep, hands-on knowledge of modern scene representations, for example Gaussian splats and radiance fields, and the ability to weigh their trade-offs. - Research experience across the reconstruction spectrum, from per-scene optimization to feed-forward models. - Deep understanding of multi-view geometry, camera models, and rendering. - Strong experience with deep learning frameworks. 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 - [ML Inference Engineer](https://feeny.ai/job/ml-inference-engineer-spaitial-london-b3wak2tt1hr4) — London, United Kingdom - [Research Engineer - 3D Reconstruction](https://feeny.ai/job/research-engineer-3d-reconstruction-spaitial-london-phyexa9qxn65) — London, United Kingdom - [Design Engineer](https://feeny.ai/job/design-engineer-spaitial-london-j54w4vx8b08f) — London, United Kingdom - [3D Content Creator & Social Lead](https://feeny.ai/job/3d-content-creator-social-lead-spaitial-london-y9zs6n0dk1b4) — 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 Scientist - 3D Diffusion](https://feeny.ai/job/research-scientist-3d-diffusion-spaitial-london-f21y5vjxxmzm) — London, United Kingdom