MLOps Engineer – Data Platforms & ML Platform Strategy (Remote)

Oliver Bernard United Kingdom
Remote
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AI Summary

Join the Data Platforms team as an MLOps Engineer to design, build, and support scalable ML platforms for production AI capabilities. Design and deploy high-quality platforms, support CI/CD tooling, and help define the ML/AI strategy and roadmap. Requires hands-on MLOps experience, cloud knowledge (AWS/Azure/GCP/OpenStack), DevOps, Linux, and programming with Python, Ruby, or Perl.

Key Highlights
Fully remote role within a Data Platforms team developing production ML platforms.
Design, deploy, and support scalable ML platforms; define ML/AI strategy and roadmap.
Requires MLOps/ML experience with cloud services (AWS/Azure/GCP/OpenStack) and DevOps tooling.
Key Responsibilities
Work in the Data Platforms team to design, build, and support Machine Learning platforms to deliver AI capabilities.
Design and deploy high-quality, scalable platforms for running production Machine Learning software.
Help define the overall strategy and roadmap for ML and AI and supporting platform deployments and CI/CD tools and processes.
Technical Skills Required
Python Ruby Perl Bash Linux Kubernetes Docker Terraform Ansible GitOps REST FastAPI TensorFlow PyTorch Apache Spark MLlib Kubeflow AWS Microsoft Azure Google Cloud Platform OpenStack Observability Infrastructure as Code CI/CD
Benefits & Perks
Fully remote work
Salary: £100K per year

Job Description


MLOps Engineer - £100K - Remote


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.


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
  • 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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