ML Platform Engineer - Hybrid (AWS, Kubernetes, MLOps)

Cedar Recruitment

Greater London

Hybrid

GBP 90.000 - 110.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

Hybrid work arrangement

Zusammenfassung

Cedar Technology, supporting a major financial services firm, is hiring a Machine Learning Platform Engineer to build a shared ML platform for production deployments at scale. The role emphasizes security, governance and reliability within a regulated environment, with hybrid work in the Greater London area.

You will design cloud-native ML infrastructure on AWS and Kubernetes, create scalable environments for training and inference, and automate tooling with Kubeflow, Ray, IaC and CI/CD.

Qualifikationen

  • Strong foundations in platform or infra engineering for ML workloads.
  • Experience supporting production ML workloads in regulated environments.
  • Proficiency with AWS, Kubernetes, IaC, Python and CI/CD.

Aufgaben

  • Build and evolve cloud-native ML infrastructure using AWS and Kubernetes.
  • Develop scalable environments for model training, deployment and inference.
  • Improve developer experience with automation and self-service tooling.
  • Support orchestration and distributed workloads with Kubeflow and Ray.
  • Establish reliable CI/CD workflows, observability and deployment processes.
  • Balance productivity with security, resilience and governance in a regulated setting.

Kenntnisse

Platform engineering
ML infrastructure
Production ML workloads

Tools

AWS
Kubernetes
Infrastructure as code
Python
CI/CD
Kubeflow
Ray

Jobbeschreibung

Cedar Technology, supporting a major financial services firm, is hiring a Machine Learning Platform Engineer to build a shared ML platform for production deployments at scale. The role emphasizes security, governance and reliability within a regulated environment, with hybrid work in the Greater London area.

You will design cloud-native ML infrastructure on AWS and Kubernetes, create scalable environments for training and inference, and automate tooling with Kubeflow, Ray, IaC and CI/CD.

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