ML Inference Engineer

Posted 25 Days Ago
Be an Early Applicant
2 Locations
In-Office
Mid level
Artificial Intelligence • Information Technology • Software • Generative AI
The Role
Build and operate inference services and APIs for production world models. Responsibilities include deploying research models, optimizing GPU utilization, memory, batching, cold starts, reliability, and cost at scale. Collaborate with research and product teams to deliver new AI capabilities and customer-specific configurations. Requires strong Python, production API ownership, containerized GPU services, and hands-on inference performance optimization.
Summary Generated by Built In

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.

Skills Required

  • 3+ years of software engineering experience in an AI, machine learning, or computer vision product environment
  • Experience designing and owning production APIs
  • Strong Python skills
  • Experience shipping containerized services on GPU inference platforms
  • Hands-on GPU inference performance experience, including profiling, memory optimization, batching, and cold-start optimization
  • Familiarity with 3D or computer vision data
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The Company
HQ: London
14 Employees
Year Founded: 2024

What We Do

SpAItial is pioneering Spatial Foundation Models (SFMs), a groundbreaking AI paradigm designed to generate and reason about the appearance and physics of real and imagined environments. SFMs possess an intrinsic understanding of space-time, enabling transformative shifts in applications at the intersection of virtual and physical worlds. Unlike existing generative AI technologies such as LLMs, image, or video models, SFMs operate natively in physical space. This significantly advances their cognitive capabilities, which mimics human understanding. SFMs promise to revolutionize various applications across industries, from creating immersive virtual worlds for gaming and entertainment, to advancing CAD engineering and construction, to powering next-generation VR/AR experiences, and enabling sophisticated, physically-intelligent robotics.

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