
Platform Engineer
AI
CuspAI is seeking a Platform Engineer with strong Python coding, DevOps and cloud platform expertise to build and maintain the ML infrastructure platform that powers their AI research teams. The role involves designing cloud-native Kubernetes platforms, owning the MLOps stack, scaling distributed ML training, and ensuring platform reliability. The ideal candidate has deep experience with ML workloads on Kubernetes, multi-cloud platforms, Infrastructure as Code, and GPU infrastructure.
What you'll do
- Build the ML Infrastructure Platform: Design and implement a cloud-native platform on Kubernetes that enables researchers to easily train, evaluate, and deploy models without worrying about infrastructure complexity.
- Own the MLOps Stack: Implement and maintain CI/CD pipelines, model registries, experiment tracking systems, and deployment automation - the full lifecycle of ML operations.
- Scale Distributed ML Model Training: Build infrastructure to support distributed training across many GPUs, implementing solutions for data pipelines, checkpointing, and resource optimisation.
What you need
Must-have
PythonGoKubernetesAWSGCPTerraformHelmKapitan
Nice-to-have
FlytePantsSlurmPBSTritonTorchServeKServeHPC environments
Soft skills
collaborationautonomycommunicationproblem solvingmentoringadaptability
Platform EngineerML InfrastructureDevOpsMLOpsKubernetesAIMaterials ScienceCloudPythonGo