Machine Learning Infrastructure Engineer

This role is for an ML & Cloud Infrastructure Engineer at SpAItial, a frontier AI startup focused on 3D foundation models. SpAItial is developing a frontier 3D foundation model that combines AI, computer vision, and spatial computing to influence how industries generate and interact with 3D content. The team is research-focused, small in size, and moving quickly toward a public demo later this year.

Note: Do you want to own the ML infrastructure at a frontier AI startup? Have you built cloud and ML systems from scratch, not just maintained them? Are you ready to shape the backbone of 3D generative AI?

Key Responsibilities

• Design and deploy scalable, high-performance cloud infrastructure for ML workloads
• Build and manage GPU clusters, storage systems, and distributed training environments
• Set up and optimise containerised workflows (Docker, Kubernetes, Terraform)
• Implement robust monitoring, incident response, and CI/CD practices
• Collaborate closely with researchers to integrate and scale experiments

Qualifications / Requirements

This person must have experience building ML Infrastructure and cloud architecture from scratch

• Working Model: On-site, London

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Research

Industries

• Technology, Information and Media and Software Development

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