Infrastructure & MLOps Engineer

Requirements

• Knowledge of Python
• Familiarity with cloud services (e.g. AWS)
• Experience managing or developing in Linux environments
• Understanding of CI/CD principles
• Experience using Kubernetes (k8s)
• (Desirable) Experience maintaining machine learning applications
• (Desirable) Experience deploying ML orchestration tools (e.g. NV Ray, KFP, SkyPilot)
• (Desirable) Experience managing ML accelerator hardware (e.g. DCGM)
• (Desirable) Experience with Infrastructure as Code (IaC) tools (e.g. Terraform/OpenTofu)
• (Desirable) Experience with GitHub Actions
• (Desirable) Experience with modern observability tooling (e.g. Prometheus)
• (Desirable) Experience with Grafana
• (Desirable) Knowledge of Go/Java/C++ (or similar language)

What the job involves

• Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure
• You will develop essential tools and services that empower our broader software team
• Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components
• Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems
• The Software Infrastructure team provides critical platforms and services for software development teams across the business
• Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems
• We operate in squads, fostering a culture of service ownership and empowerment for our engineers
• We focus on long‑term engineering solutions and strive to eliminate toil wherever possible
• Develop, own, and maintain tools and services to support AI research and engineering teams
• Deploy and maintain services with Kubernetes and Docker
• Manage our Cloud Infrastructure using tools such as Terraform

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