Machine Learning Infrastructure Engineer

New Yesterday

Job Description

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?


SpAItial is pioneering the development of a frontier 3D foundation model, combining cutting-edge AI, computer vision, and spatial computing to redefine how industries — from robotics and AR/VR to gaming and film — generate and interact with 3D content. Backed by £13m in seed funding, with half allocated to compute, SpAItial is a 10-person research-focused team moving fast towards a public demo later this year.


We’re looking for a ML & Cloud Infrastructure Engineer to take ownership of our entire ML infrastructure. This isn’t a ticket-handling MLOps role — it’s a chance to build the systems that will power frontier AI research and production at scale.


Key Responsibilities:

  • Design and deploy scalable, high-performance cloud infra 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


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


Key Details:

  • Salary: £100k–£130k (flexible for strong profiles)
  • Working Model: On-site, London
  • Tech Stack: AWS/GCP/Azure, Kubernetes, Docker, Terraform, Python, MLflow/Prometheus/Grafana


If you want to shape the backbone of one of Europe’s most ambitious AI startups, we’d love to hear from you.

Location:
London
Job Type:
FullTime
Category:
Technology

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