ML Inference Engineer

Spaitial·Londonmid

In short

→Engineer de inferencia de ML que construye y optimiza APIs de servicios de modelos de mundo 3D.
→Trabaja día a día con modelos de investigación, despliegue en GPU y mejora del rendimiento en producción.
→Destacado: Tirar modelos de frontera a servicio con alta escala, rendimiento y costo eficiente.

We are an English-speaking company. All roles are conducted in English.

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The questions they'll ask you

1. ¿Cómo optimizarías el uso de memoria en inferencia de un modelo 3D sobre GPU?

🔒 +7 more questions

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💵 USD · Remote · No visa

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What they ask for

✓3+ años en ingeniería de software en entornos de IA o visión por computadora.
✓Experiencia comprobada en diseño y propiedad de APIs en producción.
✓Habilidades sólidas en Python y despliegue de servicios contenerizados en GPU.
✓Experiencia práctica en optimización de inferencia (profiling, memoria, batching, cold start).
✓Conocimiento en datos 3D o visión por computadora es una ventaja.
✓Capacidad para colaborar con investigadores y traducir modelos a producción.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonGPU inference platformsContainerized servicesModel deploymentPerformance profilingMemory optimizationBatchingCold start optimizationAPI development3D data

Who should you write to at Spaitial?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

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 own the backend that serves our world models. You will build and run the inference systems behind our product and API, turning frontier research models into fast, reliable, and scalable services. This is a hands-on role for someone who has already owned production APIs in an AI system and can work closely with researchers to bring new models to users. Responsibilities Own the inference services and APIs that power our product, from request to generated output. Optimize serving performance, reliability, and cost at scale. Maximize GPU utilization and minimize device memory footprint. Apply latest techniques for improving inference performance. Deploy research models as production services, including customer-specific configurations. Work with research and product colleagues to bring new models to users. Key qualifications 3+ years of software engineering in an AI, machine learning, or computer vision product environment. Experience designing and owning production APIs. Strong Python, and experience shipping containerized services on GPU inference platforms. Hands-on GPU inference performance work: profiling, memory, batching, and cold start. Familiarity with 3D or computer vision data is a strong plus. 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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