About the role Join the Software Infrastructure team to scale and manage systems that support our AI compute stack. You will build tools and services that streamline the development, testing, and deployment of Machine Learning software components.
- Develop and maintain services for AI research and engineering groups.
- Manage cloud infrastructure using Terraform.
- Deploy and operate services within Kubernetes and Docker environments.
- Support the productization of Machine Learning software.
Requirements
- Proficiency in Python.
- Experience with Linux environments.
- Familiarity with cloud providers such as AWS.
- Understanding of CI/CD principles.
- Experience with Kubernetes.
- Practical knowledge in at least one of the following: maintaining ML applications, deploying ML orchestration tools (e.g., NV Ray, KFP, SkyPilot),
or managing ML accelerator hardware (e.g., DCGM).
Nice to have
- Experience with Infrastructure as Code tools like Terraform or OpenTofu.
- Proficiency with GitHub Actions.
- Knowledge of observability tools including Prometheus and Grafana.
- Programming experience in Go, Java, or C++.
Skills & tools
- Python
- Kubernetes
- Docker
- AWS
- Terraform
- Linux
- CI/CD
- ML Orchestration (NV Ray, KFP, SkyPilot)
- ML Hardware Management (DCGM)
Benefits include a market-competitive salary, flexible working arrangements, generous annual leave, private medical insurance, a health cash plan, a dental plan, and a pension scheme with up to 5% matching. The package also includes life assurance, income protection, a parental leave policy, and an employee assistance program covering mental wellbeing and bereavement support.
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📌 Infrastructure and MLOps Engineer (Cambridge)
🏢 Graphcore
📍 Cambridge
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