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SpAItial

Research Scientist - World Models

London; MunichOnsite · United Kingdom
FullTime · Engineering
POSTED 5 FEBVERIFIED 1D AGO
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Role
276 days opentrue age
Posted 5 Feb
Pay
£102k–£348kno pay posted
Market p25–p75
£102k–£348k
London · n=20 · 365d to 6 Nov
CompanySpAItial →
15open roles
Opened · 30d
+0
Closed · 30d
−0
3d of snapshots · 30d window
Market
3,285open · ML / AI
All ml / ai
6,676open
All tracked boards · live 8 Nov · n=3,285
Visa
✓licensed sponsor
UK licensed sponsor
✓Worker (A rating)
Checked 3 Nov
PyTorchLLMs

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 individuals who are bold, innovative, and driven by a passion for pushing the boundaries of what’s possible. You should thrive in an environment where creativity meets challenge and be fearless in tackling complex problems. 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 the AI revolution in generative AI technology, and we want you to be excited about shaping the future of this dynamic field. 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.

Responsibilities

Architect generative world models that reason about space, time, and physics.

Design and develop image/video diffusion foundational ML models.

Large-scale distributed model training on top of distributed cloud infra.

Develop demos showcasing the trained model prototypes.

Processing and maintaining large data for model training.

Productionizing models, test-time model optimization.

Key Qualifications

PhD in Computer Science or related field with a top-tier publication record in ML, Vision or graphics (CVPR, ECCV/ICCV, NeurIPS, SIGGRAPH, etc.).

Strong knowledge of generative models such as image or video diffusion.

Strong knowledge of cutting-edge architectures including diffusion transformers (DiT).

Rich experience with deep learning frameworks such as PyTorch.

Expert coding skills, and ability to rapidly iterate through ML experiments, including usage of modern AI coding tools.

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.

Source · SpAItialFirst seen 2 NovOriginal ↗