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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML & Cloud Infrastructure Engineer - **Company:** Harnham - **Location:** London, UK - **Experience:** Expert - **Salary:** £140,000.0 - £160,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Bash Shell, Big Data, Cloud Computing, Cloud Database, Cloud Engineering, Continuous Integration, Data Visualization, Distributed Computing Environment, Monitoring of Systems, Python (Programming Language), Windows PowerShell, Prometheus, Circleci, Scripting, Google Cloud, Pytorch, Grafana, Jupyter, Containerization, Kubernetes, Multiaccess Edge Computing, Terraform, Docker - **Published:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815047113-ml--cloud-infrastructure-engineer ## About the Role * 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 ## Description 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. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Kubernetes dev is fun, but setup and ops isn't! 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