ML & Cloud Infrastructure Engineer

Overview

This range is provided by Harnham. Your actual pay will be based on your skills and experience - talk with your recruiter to learn more.

Role: ML & Cloud Infrastructure Engineer Salary: £140,000 - £160,000 + Equity Location: London - Hybrid (3-5 days a week)

Our client is pioneering a frontier 3D foundation model at the intersection of AI, computer vision, and spatial computing. Their mission is to transform how industries from robotics and AR/VR to gaming and film create and interact with 3D content. The role is to design and maintain scalable infrastructure powering cutting-edge machine learning workloads and production systems in a fast-moving startup environment.

Responsibilities

• Building and maintaining scalable cloud infrastructure (AWS, GCP, Azure) for ML workloads and APIs
• Setting up ML nodes for distributed training and local development
• Managing containerised environments (Docker, Kubernetes, Terraform)
• Optimising storage for big data pipelines supporting ML workloads
• Monitoring systems and responding to incidents, ensuring reliability and performance
• Working closely with ML engineers and researchers to integrate infra with production workloads

What you’ll bring

• 6+ years’ experience in cloud engineering, ideally with ML-related workloads
• Proficiency in scripting (Bash, PowerShell, Python)
• Start-up/Scale-up Experience
• Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes)
• Experience in automating deployments and orchestrating cloud environments

Nice to have

• Python (Jupyter, PyTorch), monitoring tools (Prometheus, Grafana), cloud databases (RDS, Aurora, Spanner), CI/CD tools (CircleCI), and data visualisation experience

This is a unique opportunity to join a visionary team redefining AI in 3D, with the chance to make a real impact at the cutting edge of spatial computing.

• 6+ years’ experience in cloud engineering, ideally with ML-related workloads
• Proficiency in scripting (Bash, PowerShell, Python)
• Start-up/Scale-up Experience
• Strong cloud skills (AWS, GCP, Azure) and containerisation (Docker, Kubernetes)
• Experience in automating deployments and orchestrating cloud environments