Research Engineer - 3D Reconstruction

Spaitial·Londonmid

In short

→Ingeniero de investigación que mejora la reconstrucción 3D usando técnicas punta como Gaussian splats y campos de radiancia.
→Día a día: implementa métodos de reconstrucción, optimiza representaciones y evalúa resultados en benchmarks reales.
→Lo destacado: tienes libertad para elegir y desarrollar métodos desde la investigación hasta su integración en sistemas de producción.

Proficiency in English is required for collaboration with international teams.

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The questions they'll ask you

1. ¿Cómo ajustarías los priors en un modelo de campos de radiancia para mejorar la reconstrucción de materiales en escenas con poca iluminación?

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💵 USD · Remote · No visa

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What they ask for

✓Conocimiento profundo de representaciones de escena modernas (Gaussian splats, campos de radiancia)
✓Experiencia práctica en reconstrucción 3D: optimización por escena y modelos feed-forward
✓Dominio de geometría multivista, modelos de cámara y renderizado
✓Habilidades sólidas en frameworks de deep learning para experimentos a gran escala
✓Capacidad para implementar métodos de papers científicos en código funcional
✓Capacidad de diseñar y ejecutar evaluaciones rigurosas con benchmarks públicos e internos

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Gaussian splatsradiance fieldsmulti-view geometrycamera modelsrenderingdeep learning frameworkslarge-scale experimentsoptimization strategiesloss functionsbenchmarks

Who should you write to at Spaitial?

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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 Engineer to push the quality of our 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, build it, and then make it better. This is a hands-on role for an engineer with deep reconstruction knowledge and strong coding skills. Responsibilities Advance the quality of 3D reconstruction, from research ideas to working methods. Work across the full range of reconstruction problems, including geometry, appearance, materials and lighting, sparse or incomplete observations, dynamic scenes, and large-scale environments. Build and improve reconstruction methods across the full spectrum, from per-scene optimization to feed-forward models. Stay at the frontier of scene representations, implement new ones as they appear, and adopt or extend them where they win. Tune losses, priors, and optimization strategies to 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 Bachelor’s or Master’s degree, or equivalent experience, in computer science, computer vision, graphics, or a related field. Deep, hands-on knowledge of modern scene representations, for example Gaussian splats and radiance fields, and the ability to weigh their trade-offs. Hands-on experience across the reconstruction spectrum, from per-scene optimization to feed-forward models. Solid understanding of multi-view geometry, camera models, and rendering. Strong experience with deep learning frameworks, including large experiments and comparisons you can defend. Strong coding skills, and the ability to take a method from a paper to a working implementation. A PhD or publications in reconstruction are a plus, not a requirement. 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.

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