Senior MLOps Engineer (KubeFlow)

Oliver Bernard United Kingdom
Remote
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AI Summary

Implement cutting-edge Machine Learning solutions for a global SaaS company. Design and develop scalable platforms for production ML software. Ensure high-quality deployments and strategic direction for ML and AI capabilities.

Key Highlights
Design and deploy scalable Machine Learning platforms
Lead strategic direction for ML and AI capabilities
Develop and support high-quality ML software deployments
Technical Skills Required
Kubeflow Spark MLlib Tensorflow PyTorn REST FastAPI Docker Kubernetes Terraform Ansible GitOps Python Ruby Perl Linux AWS Azure GCP OpenStack
Benefits & Perks
Salary range: £75,000-£95,000
Fully remote working
Positive company culture

Job Description


MLOps Engineer - KubeFlow - £75K - £95K


Our client is a leading software as a service (SaaS) company, building cutting-edge solutions for trading, egaming and payments all over the world.


Offering fully remote working, they’re looking to hire an MLOps Engineer with experience of KubeFlow.


You’ll work in their Data Platforms team and be key in the design, building and support of Machine Learning platforms to deliver the power and scale of AI capabilities.


Work will include the design and deployment of high quality, scalable platforms for running production Machine Learning software, helping define the overall strategy and roadmap for ML and AI and supporting platform deployments and CI/CD tools and processes.


You’ll need a positive, growth, mindset, great experience of ML frameworks and software delivery and good knowledge of DevOps, MLOps and Security.


Requirements:


  • Proven Machine Learning and MLOps experience
  • Commercial KubeFlow exp
  • Good knowledge of Cloud - AWS, Azure, GCP, OpenStack etc
  • Solid DevOps experience - Kubernetes, Observability, IaC, CI/CD etc
  • Coding skills using Python, Ruby, Perl etc
  • Strong understanding of software development, modern tech and frameworks
  • Solid Linux knowledge


Tech / Tools you’ll be working with (some of them!)


  • Kubeflow
  • Spark / MLlib / Tensorflow / PyTorn
  • REST / FastAPI
  • Docker / Kubernetes
  • Terraform / Ansible
  • GitOps
  • Python / Bash

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